{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# TensorFlow 教程 #08\n",
    "# 迁移学习\n",
    "\n",
    "by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)/[GitHub中文](https://github.com/Hvass-Labs/TensorFlow-Tutorials-Chinese)\n",
    "/ [GitHub](https://github.com/Hvass-Labs/TensorFlow-Tutorials) / [Videos on YouTube](https://www.youtube.com/playlist?list=PL9Hr9sNUjfsmEu1ZniY0XpHSzl5uihcXZ)\n",
    "\n",
    "中文翻译 [thrillerist](https://zhuanlan.zhihu.com/insight-pixel)修订[ZhouGeorge](https://github.com/ZhouGeorge) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 警告!\n",
    "**这份教程使用的TensorFlow的版本不是v1.9，由于PrettyTensor构筑API不再被Google开发者更新和支持。更新这份教程将花费大量的精力，特别是在教程 #10里使用了利用keras API实现更高级的迁移学习版本。然而，你可能还要观看教程 #08 的视频，因为它关于迁移学习的解释比教程 #10 更详细。**\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 简介\n",
    "\n",
    "在前一篇教程 #07 中，我们了解了如何用预训练的Indeption模型来做图像分类。不幸的是，Inception模型似乎无法对人物图像做分类。原因在于该模型所使用的训练集，其中有一些易混淆的类别标签。\n",
    "\n",
    "Inception模型实际上能够从图像中提取出有用的信息。因此我们可以用其它数据集来训练Inception模型。但如果要在新的数据集上训练这样的模型，需要在一台强大又昂贵的电脑上花费好几周的时间。\n",
    "\n",
    "相反，我们可以复用预训练的Inception模型，然后只需要替换掉最后做分类的那一层。这个方法叫迁移学习。\n",
    "\n",
    "本文基于上一篇教程，你需要熟悉教程#07中的Inception模型，以及之前教程中关于如何在TensorFlow中创建和训练神经网络的部分。 这篇教程的部分代码在`inception.py`文件中。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 流程图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "下图展示了用Inception模型做迁移学习时数据的流向。首先，我们在Inception模型中输入并处理一张图像。在模型最终的分类层之前，将所谓的Transfer- Values保存到缓存文件中。\n",
    "\n",
    "使用缓存文件的原因是，Inception模型处理一张图要花很长时间。我的装有Quad-Core 2 GHz CPU的笔记本电脑每秒能用Inception模型处理3张图像。如果每张图像都要处理多次的话，将transfer-values保存下来可以节省很多时间。\n",
    "\n",
    "transfer-values有时也称为bottleneck-values，但这个词可能令人费解，在这里就没有使用。\n",
    "\n",
    "当新数据集里的所有图像都用Inception处理过，并且生成的transfer-values都保存到缓存文件之后，我们可以将这些transfer-values作为其它神经网络的输入。接着训练第二个神经网络，用来分类新的数据集，因此，网络基于Inception模型的transfer-values来学习如何分类图像。\n",
    "\n",
    "这样，Inception模型从图像中提取出有用的信息，然后用另外的神经网络来做真正的分类工作。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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DE45xwgknTHr85cuXjyvb4dq5cycAQRCwaNGiptvMmTOH9vZ2IFl1YF/7WwWhWb0eSKFQ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2zZsJQ33vmAf937MN26dsRxHXy2Dyk9wIrsNRRWOLRJa0vdOgl8//0mHMLZtG4tcU1b0Dq1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AqFQqG4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\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ci7PTgMUsdcnOQmTIVAciYvR2iXphQgCDBsKBuHxRFvIDNE9fV9SE8PLVq//razlP7z19\nMdRuou8lA1IuyLk0GQGh+QW7UgmEQxYvFM4WjB7eeru/UmhB4XJNk56G4XAgrNlSPjUJrFbwTJHF\nENHQSpSWel04hUg5DyZPDM49+8hUEg9PL+rU/Re/7j3I9r/+vpW3q0Jxw2RnZ5OUlMSWLQWXdnL2\n7FnV/kuhUCiKIcoBoFAo3HjjjTdYsGABn376Kb179y5sdW6cazkrtCtOvp0n4nkK7uV3nzNM3uFe\n6C5f8jtZ1tfCgVuYvctJwVVOuLlKMburLZv7hDvXpdzh7Vc+h2vyTyIANJeYewTAldETV96u4VZQ\n0VmEUNPncd1+Ld2vs7fcz8htTuf13FEUquCfonAJCQmhfv36eXqC30769++PyaS+Bt7NpKam8scf\nfzBhwoQCW2P37t1Fs/ivQqH4x6i//AqFwg1PT0/effddXn31VTp37oy/v39hq3Rt9N7zwmoBhGzR\nZ7XIU3NvPwDZVs/kATYrwiJzzQ2Rejs7TdPz2jXw9JD/ZqQgsjNlUb6AECnnLMjnE4hm8srJK9eQ\n89os8t60i9IW9fKV7fu8NLSoSvopuCeapiFMJrSQcL0GgP5n2G7LiQBwouk56TYr4swxQMjTfocD\nfAPRgiNyZD29wW5D01MdRGaa1CO8jKxBoJFzYp+72r3BIPW223IMbk9vqZvNIn/38JYt+7z89OJ6\n5EQ/aBqa0Sh1y0oHg15Q0FNGBYjzsjUgvgG6vkK+Fs79aRoi5RLWrxaCw47pviYYKlbBfnA/tp9+\nQAsOxbNzdxmNYDDIQoBCIDIuy7m8/eWJf8oFROJROW90NRnVoWlyLQFacLh8vkZTTlqHs26A0STr\nOXh4yeKITpzdD5zRHwqFQnEHEUJgs9kwm80FtobdWaNGoVAUG5QDQKFQ5OHJJ59k9uzZDB06lOnT\npxe2OtdG6AaaM9Q7+ZwMWTcY0QKCAQ3CogAPGTpvyZIGX3C4vGYxy3BycIWmi+wsSE9BoKG5HAC6\noWw05RSKs2TJA2WHPafQn64HJi/wNIBmRAspCYCmG56awYjwDdAdALox6iywp2k5IfJGgzTa7XZE\n6gU5b0aKrKpvs8q0AJAGu1F3XjhPsi1Zcq2AkJwoBmOuP/lXpEm4RTjo6RRYzVIvLx/pBPDQ/9tt\nrlz5+1b9S6pvkEtOZKVDdqZMJ/HXQ/lNnq5bAURmBrYtP4DNiqFiFQxVa+G4cAHr5h8xRJXG8/FO\nMmzf5CmfK0K+xs7iiHYr4nIy4vRhOW1YFDjTOpzP0idA3pe7FoTdDsIuXwMPT/1HLxCod0AAZwSF\nigpQKBR3luDgYOLi4vj3v/9dYGucPXv2rk/3UygUtxflAFAoFPkyd+5catWqRbt27Xj00UcLW538\nEQJx8QzC20c36PWTXqtFOgB8A6VNnJ4iDT+jUeadawa9srwmzTqnQZqZBghIOoO4eBYtUkBEtGst\nXL3sbboxrrcCMuRUj9c8vAGByM6UefYGI5pPgNTDN1Aa/0LInH3A1THA5JnrZFrfn8OhV+JHnp4L\ngcjOAJvI6XTglMMK6B0KHA6wyjZGsu3gFaHtBudz0HKq+ueucu806N1SBvSweeeakON8yc7Q8/Iz\nQDhkhIS37iQxZ8rIAJ8A3bgWOW0APbyl/8DXH1PTeHDYMZSMAuHAEBmFR4uH0IJC9FoEhhyDH+Rr\n6zTordng44cWXVXO6+2rdybQXy+Qz1EI6bjQ9IgFu+xQoHl4I/w0V3SBXMAImpBtJpw1EBQKhUKh\nUCiKOMoBoFAo8iUqKoqxY8cyYMAA/vjjDwICAq5/0x1HIE7sRwSGYIgsJ43ByPLSMNUMMgwfsB/e\nDdlZaCERGKIqSWPVeVqtafK0WghE0in577EDiNNH0YSGVq2BXMluyzmld0UbnJWF6EqUkafbIIsR\nahri2B5E0mkZgh4WJUPlPX0RHtL5IJxF8gz6Kb/BhKsdXbY8vZeRDfpeSsmUBZF8Vuph9MgJpbfZ\npIHq4S1D8+1WWaxPCDSjCRyGnPkgpxWeNRuyM+WYp36yT05Iv9AM0ggGPW9ec3c6OBwyPeFysiy4\nl5QINiuaXwhaUAkpdzkF0lPAPxTNxz+XboB3gFwvOA0+rZkAACAASURBVBTP3i9Lef1E31i1Bsaa\n/9LD9LNz9NedB1qITH8Q1myEORMtIAStdGU5lpkmUyAgR19nyz8Pr5wIB6dTwMcfzRSC9NLoDgOj\nUf7ucMgIET2iQqFQKBT3LufPn2fNmjXs3buXc+fOkZ2dTWRkJHFxcXTq1AlPT8/rT3ILJCQksGrV\nKv766y/Onz9PYGAg0dHRxMfH31J3pqNHj+Lv709ERMT1hRX3PPk0klYoFApJ//79qVatGl27dlV5\nggqFQqFQKO5ptmzZwquvvsqff/6J0WjE39+fXbt20b17dypXrsyhQ4cKZF273c7QoUMpV64cw4cP\nJyEhgZCQEAwGA+vWraN58+b/uG2nEIKKFSsycODA26y1oqiiIgAUCsVVMRgMLFmyhCZNmvDqq6/e\nhfUANLSyVdC8fRCZl2U4uTO0XQjXKbAWGCbz5n38EQ4HWLIQJ/bJ017fAHC2jwvR88brNkarVBeC\nw2QVfZAn/3YrZF6WLeM0Teaao4GPnyuXXugh9VpopKt1n2Y05YTTCwcYTGgR0fIU3G6D7Ex5sp+R\nBh5eMkoBZMs7mxUsmYhje+SJvpePDHH3zVWc0dlJwFWM34jmG4QsuCcLFgq7jaQZM7FduEDwk0/i\nE9uA3BXxnfUJ3Mrj6wUWsZjlv0aTnoOPXnTfiPDwQguJlPMYjFLO21fWRQC0yvX0qIBAmfqgGWSN\nALlDWZfBbkekJ+uq60X6jHqagx5l4Ar3d9Ye0E/2NWf6htEoW/6BjIwwmuS9zpN7L19X/QFNL7wo\nhD0n3cIZ+u9sM5hwSKaSGPWCjT53YwSMQqFQKG4njzzyCJcuXcrTIWP+/Pn06tWL0aNHs3jx4tu+\n7vPPP8/8+fPp0aMHH330UZ6oy2PHjjFy5Mjbvq6ieKIcAAqF4poEBASwatUqmjRpgo+PD5MmTSps\nlXLQNLSQkmgeHrqhp8lq9UZTjuGKkKHnmjPH2wE2i+wWIBwQVALN2w9XsUBNQ/MPyVnDZRjaZei+\nJQtx+ZIMyy9bVS8ql6uwnMMu7/ELkgX4hCMnzN5ZZd9gQAsIlWPmTKlr2kVZwNDHH2JqSHEbsruA\nzSIr3AsHWqU6MmXB09vtObjl6xu0K4r1yTZ7l3/ahuXYMXwbNsInNjanroHI1Z4wN/qeZai8MzTe\nQ19SVuXXMCH8dGeD0B0GHp6u3HstMsZ9Xu3/2TvvOKuqc38/a586Z870YaiDI0VQLAiKgkEsoNgu\nYO8XE/u1pnhtQaMxmlhSNPeaaExMovmJscREc+2J1wixYaNJkT6U6X1O2ev3x7v23mcKiIbqXc/n\nQ4bZZ+2111p7gvO276uCcgPvrLIZ0V/QWpwpEa/LglHf93QKQirQSfDmDIXFGeA5K0AcAN61zlZz\nTTQWVDgalAV47zaTMuURGlwN2kXXVkNHK8TzUQP27HreFovFspNZu3YtjY2NDB8+nEgk8rnjm5ub\n2bRpE5FIhMrKyh2wwt2TRCLR63VPC6m2tnabP/PVV1/l0UcfZfLkyfz617/GcXomaO+55548/vjj\n/vfNzc088MADvP7666xdu5ZMJsMee+zBuHHjuPbaaykrk048Cxcu5KqrrgLg9ddfZ8qUKf4czz77\nLPn5+dt8P5ZdH+sAsFgsn0tlZSWvvPIKkyZNQmvNPffcs8uoBmuvTZt8hx/V1jnR37Db1cBVIYmi\na42KxgOD0DPUIzGpyc/dYjYdKM/HEoF6vixC5tZAU70YogXFxgg3RqsG2poDoxMCUT2lpH4/LykR\n/pToE+hMSroUpFNSk64dmUs5ErH3RQPdoL1fNkMX8Tvl+mOiA/qDzuIkzX/wlWdQ55yNzhHp88Z0\nd3BAIBSY+3cnhN9i0B/nza0DJ4J/sNpMoYN34LVbdI3jRNPtzMy96ZysAO8c/DW6wc9AKCxzGM0F\nHYqgnJAsIZYw5+llZ5iz1BoVS6CVkvfhzWexWCw7mQULFjBjxgw+/fRTQJz0P/3pT7ngggt6Hb9m\nzRomTpzIypUr0VozZMgQli1btiOXvNvT3NzMbbfdhuM4XHTRRdt8fs+wv/zyy3s1/ntj48aNvPzy\ny5x00kn069cPrTUfffQR999/P0888QTz5s3za/4vuugiXnnlFYYOHcrFF1/sz7G99Qwsuy7WAWCx\nWLaK4cOH88orr3DMMcdQW1vLww8/3CNFboejNdnmOrKxOCGjOq+zRqG/oxV3hUnzzyuQ6G9JX1R+\nEcTzcUYeInP4xp/GXThXjL9BIySF3wn5Ked601p07TpU2YDg3nSHRL3djN8vPvvSH6CxDmfSdNTI\nMZIqHy+Qz+b8VQTxlIJYHBwH56ApkCjAqRolz0t14K5aaObvlDZ6AIWSMaDiJkIeS8i8gE61i9Ge\nTUnnAS/bAXxHhQIG3X2HXAtHxUB3QhDPKSUAyKRwq5fLPQUlRmwwGmRVmLIKHc8HTDmAyTZQntGd\nMw4jikgmJesMhY1AoBIj3jgF/IyIaB6EI+jatVKmEYnhDNrLpO9HxFGiNbp6ubyrkr5SUuA4QSeD\ntiZxooTCqKI+4Lpk5z4vXRs8Z4bj4IyVs5f3HJEzaRUnkBp5sDgKshmyDRtxO9q+0I+mxWKxbGu0\n1px88sl8+umnPProo0ycOJGjjjqKiy66iAMPPJDRo0f3uCeZTHLTTTcRiUSYOXPmjl/0bsqvf/1r\nvvWtbwHQ1tbGoEGDePHFF5k8efI2f5bnzNl///23+p6hQ4fy2muvdbl29tlnM2nSJI4//nj+8Ic/\ncNFFF1FWVsZpp53GGWecweDBgznttNO26dotuyfWAWCxWLaaffbZhzlz5nD88cdzwgkn8Nhjj1Fe\nXr7T1qO15u2PFjCof1+GDh2G8lrFeX8cJQr4XdrZeZiodDBbEMnWrijrh8npd791KCeE9qL6PT5z\nRFnf8aLquZ7+XiLM3j4gZ75eMi+07hml9u/rMpCe+84Z731kWiR2nUD3fl+v9FJOkDuXF/X3MzY2\nM0dudH9zc23pOblXlIN2vDNX3c6+x2D/r+lMhoWLl7J81erNj7dYLJYdwOrVq1m8eDHxeJxzzz0X\nx3GYOnUqDz74IM8880yvDoDi4mIuvPBCPv74452w4t2Xww8/nF/84hfU1dWxbNkyfve73zFz5kye\nfPJJxo8fv02flUpJ1t3WlHLkkk6neemll1i8eDFr1qyhtbWVzk7RwrHv27IlrAPAYrF8ISorK3nz\nzTeZOXMmY8aM4Yknntjm/zHcWpTjMH7yccQiYZPirdF166S/eyiMs/d4MebSnfiCeKb3O3FTh55O\n+aUCztADAMi+9Bzu/Hk4+x1E6LiTZVwohEoUdK0FT5tUeccxqfwOzmFTRbSuuI/JEABt2s2pvUaj\nshkZ6+kSJIvBCcuYdMq0GDSp8p3tUL8Ronk4Q/cVozUvKeUA4SB1T69ciF6/ElXWH1U1Ulrz1awD\nNKrP4KBdYGebOAqcpDg2vBIADbrZ1DU21uH+5Q/ghAmdcRmqqATd2iit8FwX3LScfSgUlA94Rnq6\nA7JZOaeInJPubJP9xPJQiULIZtB11fIOMuZdOGGUl+EQDsvayvobDYWcsoZwxHfSKCPcKGn8IXmG\n19oxbFokGvFDtEbtPxHlul31DPLyjdBgFnRG9pJvBApNRkfEUew/9iDeXbSUOR8v/kI/nxaLxbIt\nqa6uBiA/P99PFS8qKurymWXbMHToUIYOHep/f/XVV7Pvvvty/vnnb/NOAJWVlbz99tssX76cwYMH\nb9U977zzDtOnTyeTyXDSSSdRXl5OaWmpiO0C7e22da1l81gHgMVi+cIUFRXx9NNPc/fdd3P00Udz\n3XXXcfPNN++UkgAVjohB7EVtM2kxGJWCeH5Oir+o73etWyeonQcZD+jWFvSGdejB9UEtvWfoOjnR\nZe8+rYPnJAvlnki0Zz18LGHWEZLUcwg0ALzMgy5RfC8TISvzqcDR0CXDINUh+gKFpUGE2+txjw7G\narfbM0ykXunAMZJOQWN9UDvv1fW7WWMUe5oCuutaPd0B7dJFrd+rrfeuaR2srXtrSU8vQClUKIKO\nGy2A9ma6RO2Vypnf00HIzZZwul4HcZxAjuAfge6A/w5zrnkChRDoBFgsFstOxDMOm5ubSafTRCIR\nampqunxm2T4MHDiQfffdlzfffJOGhgaKi4u32dwnnHACTz31FLNnz+aII47Yqnu+853v0N7ezuLF\ni+nTp49/feHChcyaNWubrc3y1cQ6ACwWy5dCKcV1113H5MmTOf/883n++ee5//77OfTQQ3fsQjIp\nUCbim83i/uN1dGM9qqiU0PSB4IRE8T/dKTXi8XxwQqIFgGmd5xmHxuALHTIJZ+hIVHmFH91WxX1M\nHb6SLgBo2LQW0Kjygaik/DKg0ylQxlj22tIZo1uvXyHGeiwhbQZzjVRPzNBxUOWD5HJhubQmzI34\nh8I9ygdURSXEE6hkCSqaJ0J3Jf3M+FBgyIaNU8KV1oNkM+iMieh7mQ1FZTjHnm6yA0C3NqA3rUY3\n1qKSxagyaZWoUx2SoeDV2WsXvXieOCKG7gcVsgdS7aKsHxVBPa2UcRQYjQHPoWEMb51NG02FrDgI\nlDJZF6qrwe7tK5sSh4LjBLoHqXbZV2c7LJon8w8eCtFY4KhRSs42HCFwLmgj9OjivvECtDRK5sLe\n+0omhsVisexE+vfvz/HHH88LL7zAXXfdxYQJE/jzn/9MPB7n7LPPBuDSSy9l9uzZ3H///Zxzzjl0\ndnby3HPPsWrVKgBaW1t58sknKSsr46ijjtqZ29mtWLFiBR999BH9+vWjsLBwm8597rnn8uMf/5hf\n/vKXHHnkkb3W6buuy29+8xu+/vWvA1BTU0NFRUUX4x/gwQcf7HGvUoqSkhKampq26botuy/WAWCx\nWP4lxowZw7vvvsuPfvQjJk+ezIwZM7j11lu7pM5tV7IZCBkD0tW4ny5Cb1yHqhhAyNTx6+Y6MQZj\ncVQ2LYai3xc+EojHGfV9NXQEatjeYrh7/exjBRCKoDtaoKlWDPqmGkkvL64IjE+/xZwrhi/4GQi6\noUZKFRKFfhs9M9iMN9HzAmlDqFxpU9i1lWDI7wTgU1CKiick7d70uddeKntu7b63tmxGUvnTndKG\nkJxsibwIar9xMq69WZ7bVA91G8T50F1oLxyFIonc6+qV0FgL5QNQxUYbImOi/VoyGJRSfooisfyg\nPMGLynut/9ys3OuE5F155+jhGfIZ4yyIRP216WxGHA+tjeilH8lZJROQly9tAL2MkeK+XefViDMh\nm0EvnAe1G6CgEPr2QbfZX5wsFsvO55FHHuGSSy7hvvvu4/bbb2f48OE88sgjDBkyBJDygJKSEl/h\nvaWlheuvvx7AH3P99dczZswY6wDohTPPPJNIJMJBBx1E3759SafTLFiwgIcffpj29nZ++ctfbrVS\n/9YSiUR4/vnnmTZtGqeffjpTp07lxBNPpKKiAq01CxYs4IknnmDp0qW+A2D69OnccccdXHrppZx3\n3nk0NDTw2GOP8f777/f6jCOPPJLnn3+e66+/npIS+R3jmmuuIRaLbdO9WHYPrAPAYrH8y8TjcWbN\nmsX555/PTTfdxKhRozjzzDO58cYb2WuvvT73/nXr1jFgwIB/fSEKCIcgHDZGnnfdEwF0ukSAe+Cn\n9CNp8b3hZ8976eo5H2xOzM776rXu6zWdvJfSgs2tr8f33cfniuttSbgvZw+5a3LdnPtUoBWwJeE8\nCFr4ddlfb+KL3a71tl+v/Z/3RwE6R8Cw+943d/ZOjlaB//jNiRTm3ud03Y8tAbBYLLsAffv25dln\nn93s5/feey/33nuv/31ZWZlt+/cFOO6443jqqad44IEHqK2tJZFIUFVVxZlnnsmll17KqFGjtstz\nKysrmTt3Lk8++STPPvss999/Pxs3bqSoqIjKykrOPvts3/gHuPXWW8nPz+cPf/gDs2fPZsCAAUyd\nOpV7772X888/n7333rvL/A899BAPPfQQ8+bN47333gPgiiuusA6A/6NYB4DFYtlmVFVV8dhjj/G9\n732Pu+66i9GjR3PyySdz3XXXbbG9zXnnncfChQu54ooruOiii3qktG0RNwM6DBFpHxe+8DqJcDsh\ncQKgpY2c6wZt5KCrunw2C7i4axZLRD9ZLO32QmGJLIO0sEPSw1XCpP/1GShfFeiWBvl7LCGGshfJ\nRqGMHoAzaoKf5u9nCJg2eSqaJ6nu2QxuvRFziuZJqUI6i67bAGhUokii7q0NuLXr5PEFpSaCDzrd\nIS33Nq6WLIX2FnmmcnCq9oFoHN3SKBkR4YhpyYfsF4Vua8J9+yVpkzfmKEgWoEYUinhhbilCR4uk\n3zueQyWEM/EkOftYPBiXKKSLmn84jOpTCWjJLki1SUlGslTWn5Vz02016OrlqEgM1a8q0HEwzgl3\nw0p5V/mF0oYwljR7ABWTnwUShTgzLkGj0TVrJLqfLEHlFYhfIxyVEhEv+8ArN9AaNelYyY6IRHEG\nDkGVLNj6n0mLxWKx7Jb8+7//O//+7/++U54djUY555xzOOeccz53bDgc5oYbbuCGG27o8dnLL7/c\n41ppaSn/+Z//uU3Wadn9sQ4Ai8WyzRk2bBgPP/wwt9xyC3fffTcTJ05k8ODBnHnmmZx55pk9ygPu\nvfdeJk+ezG233cYDDzzAyJEjuf7665k8efLnp9r5EWKJ6qpyk9adqwrvpa2HwtIJAIKUc7woM6b+\n24jUuZmugn9dxADFseCnr6OC+bxoORpc73uTep+X303kL+fv3j691HcwazVr8EX9zJxu1i9ZEAPf\nS2M3egKZlPw91eE7AOTenFaH3pmAv0YF0NoYRL5D4WCMzrkv9+y9NSWLgjHedU+zwMeUXaChww3W\n7piovGPOzWgoaEB5Y1zXOHx08K7iiUB80H9EjlhiMh+lNbp+PWTTKCcUvLcurRVzxSG1iDlGo0GJ\nSOiLtWeyWP4VtNa0t7ezZs2a7faM1tZW4vH45w+0WCwWy1cK6wCwWCzbjcrKSn72s5/xox/9iL/8\n5S88/vjjfP/732e//fZj+vTpHHHEEYwbN47Ro0dTUVFBbW0t1dXVVFdX8+GHH5JMJjnjjDO46qqr\nGDRoUC9P0OjOdrTSqEiOYe+r8ovhqdctlXr3glIRzAOUI//86c42dGujXOtvHBPtzRLRD4Uh3Cqf\nFZSi4vnoDWvQy6SuXI2ZFKTGG2NSGcNTK9d3Suis1Knrv/1Zou/5hThfO9YY/SJC577zd1ixGKJR\n9J57ylyxPGm/pxxUqYjvEY5IHX007kfvCYXF4A9F5E84KkKCWkN+i28c6/YW6GyTvSeKJKIf6vaf\ngWgMNfwA/M4EnW0SzQ+F5WyNsKGKxCC/WK5nxWGha9ZCJo0qLAuEFb1Widr1W/J5HQXcOa9Ca5No\nMwwZIfvsOxgKy1CxOJT2l3r8z+bLHPlFqPJ+kjHRt8rM3wmpTsns8BwNHW3SflAp0SrQGuo2iHCh\nEzLrVRDNk3u0EW30nD+AKhsg11Id6MXvQ/Vnm/9Bt1i2MR0dHbzxxhvbtUZ748aN/Nu//dt2m99i\nsVgsuybWAWCxWLY78XicU089lVNPPZWGhgaefvppXnjhBe69915SqRRf+9rXKC0t7XJPXV0ddXV1\n3Hffffz+97+nsrKS73znO0ybNo1IJCcam05J3b/OQm77O6X8aL9u2AQdrSjlQPmAnCg9Yoy2N4tR\nOWA4KCVOgQ6Tmh42Sv7JEjGE21rQny0EJ4Rz2AkmhTwnAu3Vm+fWjbtZSe1f/CHUrIeyChh/FLn/\nBOsVi9Hv/B0KClHlpqOAF72PxMQBoBTK60oQjqA9I9t1g7IHL2qfNEKCkZhZmxanhpuVz2J5cm/3\n2vZQRIxwkHNMd5pyirDMYwxkQmEpd/DKGbRGN9dLZD6vAJUw5+u3/MsEXRGMwr9etgDqayAvAXGT\nKVBQjCosFSdGsgg6WnE3rZPSi3IXyqW7gef80PUbpZzBdf296ExKxBZBug5ojW41ooWJZCAC6Bn9\nuVkLXleE/GLZW3M9bvVKEXC0WHYQeXl5HHvssfzxj3/cbs+49NJLSSQS221+y79ONptlw4YNvP32\n29vtGRs3btymLe0sFsuuj3UAWCyWHUpxcTFf//rX+frXv47rusybN4/XXnuN3/72t72Oz2azflbA\nueeeSzKZ5NBDD+X73/++DPAi8BrJ5M5kCHrRR8VojiVEP85rA5ebsg8mCp6TBh6OSP294xgdAcwz\ntKSFF5V1bUmX6fQNR7epGbJZVEEBxLy2c2JwqqJStOuivPuVE6TxR6NQVAyJ/Jzdq5z6+e4Chblt\n8RRoJ1ijZ7iDb/yjzb7cHFE8NxOUG3gZFNoN5u3iHDBGvLde37lBoHeQTslzc8/W1+rLKRfwyg0S\n+eh0pzgAEoWyrnA0yN5wQuCEIRIJNBy6p+KHTWeCULjr/OGoqWcQBwCxPJk/YrIZlNl/1hEHgufY\n6LFwgvOzWL4gl156KW+//TZXX301p59+Onl5eTt7SZadwE033cTBBx/MCSec0NWB/Tm0t7fz1ltv\ncd111223tS1ZsoSBAwdut/ktFsuuh3UAWCyWnYbjOIwdO5axY8dSXl7OhRdeiOu6mx3f2dlJZ2cn\nr7zyCh9//LEEliN56EhcbD3XlVrvdEoiyH33EMN7rzEoE/VXjqSy6/Zmf15VaFLpjeHqlA2EPpWS\ntu6tR2tJYR80DKdSOhtoJJ1dr19hasyzdDz8K3RNLbFzLyA8YaIYm0V9IBTCmXGBEQEMQV4haBd3\nyXuSZr9nFWrPPeXzVtNyLhSS9n7hiAgVKoUOZcTYd0KQV2A24Dk1MlIKkGrH/ewTER4cONwY9wpV\nOsC0S8zIWTXVoNd8CkrhDBsTGN5eC8HODhMZlwwD3VQr4wFVUiFGO6AynTJm3Qpob4GS/lBmujpo\n85mbRWfTRvCvRAzqcRNRne0Qz8cZOa5LKQUxR4z7aAwqBooRX9oPVSIZAN77U8V9oTTUNX2/oFTa\nJ8p3iHhiMidLwpSGNNfLO163HBo2QTSOqtrbOI3yIazQrks2ncHNdWpYLFvJ9ddfzwEHHMBll13G\nddddx7hx4/jWt77F4Ycfvs1biVl2Xdra2jjrrLMoKSnhmGOO4YorruCggw763PuSySQzZszg/vvv\n325ru+yyyygqKvr8gRaL5SuD/a+PxWLZJfj444+3aPyXlJRQVVXFzJkzeeutt1i5UlTg35n3IctX\nrgp6y1ss25BM1mX+2o0s31i/s5di2Q2pqqri0EMPpb29nY0bN/KXv/yFk08+mcrKSq688koWLVq0\ns5do2QHcfvvtlJSUUF1dzaOPPsrkyZMZPHgwt9xyC2vXrt3Zy7NYLP/HsBkAFotll+Cvf/1rj2uF\nhYUUFxczbtw4rrrqKg477LAuUTPlOIw/9BCisZwU8Gg8qFn31OPD0mqPVAe63YjDeWmYmZSkgKNE\nUR6FRotyPHSt4/dLC5TpGtAmn+Xlo1R/cF3C4yehW1pQg6ok8u66aCMgpxIFsjbtBmJ6ReVBGj7I\nHrw2g5GYtPdzwiZyTZCC7/Qi4AeSIu+kJdqtNTqTkuwHpYxQYFjmyKYlI8JoC+AaYTzHAYwyuGvK\nKbJGdyASg1KJwEtKvamlj8akdV7/Kkh1SGs+j3BE9uSERCDRcWQ/WqOKK4I1GSFG4vmSvm+yBkDJ\nGWktmgOeqKATBnRQApJqQ7dJ5oTKLwq6A7Q3BefllRT4P0PSMUGVVEAs328dCKBb6kFrwulODvja\nEbzflGXuP20rQMsX54ILLuDNN9+krU3+vaivr6e+vp4HHniA3//+95SWlnLxxRfzjW98g/Ly8s+Z\nzbI7kkwmGTNmDM8//zwAjY2NNDY2ctddd/HQQw8xcOBArrrqKk455RSry7AL8sYbb7BhwwYqKys5\n9NBDt/n8Wusueh+RSIRkMkleXh777LMPJSUl2/yZlv/bWAeAxWLZ6Xz00UfU1tYCkJ+fT2lpKaNG\njeKqq65iypQphMNb+KcqlpD6eTSS6l0gxq9S8hXEKaAcdFsLuno5RGI4A4bImM52dP0GSfv2jGFA\naxe/Bh+McF1ajFWvDWBrI6BxCsqgjwjnRc8ZYcZLmj1tzehF74jC/T7jxMDNupL2Dzh9q0RI0K+R\n10ENfTYjBq8n7AfQWidzR2IQTwZr066UPcQS4lBIp+RaqsPfi4rGIRQWQ9kT6xs8Up5Zt16++k4F\nrx1iNnhGPF/S60FS/dMdQTkDoEaMlc+8DgLe2ZtWhso7W5PpoQaYrgvpTvT65eIUKO0v3QWMcCKO\nEyj+u66o+0PQZcCUDejONvSGlWbeYai8JLgZXO/dlvQTAz8cDTQIPGdMssRcU6L5oF3cT9+VdxRL\n4Iw9EhZU4875hPfff3/zP4sWSy+Ew2Hi8bjvAMiloaGBhoYGZs2axd13301VVRU33HADmUxmJ6zU\nsj2ZOnUqL7zwQpdstVQq5WvcXHHFFfznf/4nhx56KFdffTWHH374TlytxePVV1/l2GOPJZvNcsYZ\nZ/D//t//2+bPcF2X008/nVAoRGGh/Pe0vj7IOtt7770555xzuPbaa62DyLJNsA4Ai8Wy0/n6179O\nNpvl6KOP5rLLLuOEE07Y+v7UXo26fNNVGC+3/7w20eJIDBWJBnXzoXBgpHpGv//7WY6Svy/Cp4NW\ng0YgUDc3QEOD2Lkl5dKVAK+vfUiiykoFEXMIshMyqaAuXZln65xneQJ0JhpOJiWGcSgc7E+ZdZt5\nNVoi4FrnOCyQTAdPKNDLisikZP72FnlWKCIGOAT3OU6wdl9oT+WsQQfP9/bmvRPltUmEHkJ6mTS+\nuGA44vlwxPGQTkFHmzw7LxxM7wkYes6dUBhUCBUKo/3OBjK3djMi+ufrI+ggE8Cby8VkOZjOESFz\nPq0txsmR9TMm2tvbOeaYY7BYvgiu69LY2LjF6aavLQAAIABJREFUMalUitraWurr6znnnHN2WHu+\n2bNn8+yzz+6QZ/1fp7W1dYufNzU10dTUxDPPPMMLL7xAcXExp5xyitWK2ImsXr2as846i7POOovf\n//732/15o0eP5t133wVE82jt2rUsWrSIBx98kJtvvpknn3yS1157rUfXJIvli2IdABaLZadz++23\n87WvfY2CgoIvfnNnG5AxhqhC5ZeIcao12ksXN8aiiidQA4cGxjhAsgRV2MfM1Y4Y3LqrUwECAzjV\nCZkWMTILysUmf+Jh3Lf/DqEwkW/ejqoYYEoFwpBfhHPQFJkj0+E7EHRLg2lP1yBrKyiTqLbWYpSD\nGNJeBL5DSgbcjash3YkqG4BTKkJ7Opv2WwHqtiYR9dvroJy9a3A17sJ/QnsraviBIpDY0YKuWSOR\n9Y/+Aa6GRBLnwHzZa35RYDArR+bKmO4C0Tyz3pxnmF9Udf0maBODR/UZLMY9KiipCEdl73XVpgQg\ngiofJGPamqB+PTTVoTethXgCZ8RBxjiPQDRfzqhuLWgj+BfPh8JSQiY7QTfX4dZXQyiM03dP0Bq3\neqmcW/kgKWXw9oBJ9+9oE4dOQamc49w3oHY9FBajkwVQs5b8/Hxqamw7QMsX47333mPq1Kmb/dkJ\nhUKUlZUxcOBArrzySs444wx+8pOf7JBsk8MPP5xLL710uz/HAi+++CI//OEPyWY3Lyial5dHPB5n\n4sSJ3HjjjTz77LO0tLTswFVaPDo7OznttNM48MADufnmm3eIAyCXWCzGkCFDGDJkCMcffzyzZs3i\n9ttv55vf/Ca/+c1vuoxdv349TzzxBHPnziWbzdK/f39OPvlkJk2a1GPezs5OnnvuOV588UWamppI\nJBIcccQRnHXWWcRiMX/c+++/z+zZs5k5cyatra386le/orq6mtNPP52zzjpre2/fsp2xDgCLxbLT\nOe644/6Fu43BrszfvdZvm6N733uvPt6bq8vXbs8hZ5xWwbNcV9oPbu5WP4KTEwbX3b5uNbqXe3rZ\nr58dYLIKlDZ9793guv98cRB0yabQ3n43c5ZeBsXmzkp3P8tuWQLeM7zn52Zb+JkP3np6u9f7H29+\n1XWINpkTuXPq3s4ud8Kcz7Qr55V7ZhbLl+Af//gHDQ0NPa6XlZVRVFTEueeeyyWXXMKAAQN2+Nr6\n9etnU813EL///e97Nf7z8/N9kdtrr72WE088kWg0CrDZ7IwPP/yQv/3tbyQSCaZNm0ZFRcVmnztv\n3jz+/ve/k0wmmT59utWZ2EquueYa1q5dy5///Ode//+7o7npppt44IEHeOKJJ/iv//ovvxTgT3/6\nE+eeey5lZWWceOKJ5OXlMW/ePH72s59xzTXX8OMf/9ifY/Xq1UydOpUVK1YwY8YMhgwZwvr167n0\n0kv52c9+xquvvurrDXzyySf88Ic/ZNGiRcydO5cpU6bQp08fW570FcE6ACwWy26MRrc0oGNxqf0H\n3A0r/JRyVWJq+p2IP943AtNeP3sHZeretVdTn2qTyHQkJjX1SFRZdzSJmF3ICNA1SUQvfOwMmDxd\nDNBEQlLGvd70KFTIkUdH4nJfOgUdreKvqKiEcFRq2xs3Sc3+8vmytD6DUEP2g0wKvXEFaI0zaLgI\n2SmFbq6T9Uaici0Ului6MvXtgFtb54sMOkP2lWvv/i/uZ4+iRozGOeJEWcchJrIeDqOKJCNCd7SC\nzqI72kS0MJ6PSpoo++rF6Lr1qFgCNfQAOeeOFjGYG2r8tanS/r5goQrH5J0Zg1rlF5osBxfdsEHW\nEU9AQSm6tQka6yCdybH/c/QRQqLD4L74R/SS+ai9D0QdfZKsrWEDuqkOIlF0VCIaTp/B4DhoJxzU\n4LY1yXypdsmiwJybcgiddpGcWygEBSVQ8skX/eG0WAD45S9/6f/SXFpaSkFBAccccwyXX345o0eP\n3smrs+wItNa89NJL/vdKKfr06UNRUREXX3wxM2fO3GrD/IUXXuCaa67hjjvuYNWqVUyYMIG5c+f2\nev9zzz3Hd77zHe644w6WL1/O+PHjefvtt62o3Ofw6KOP8qtf/Yq//e1v9OnTZ5dwAMRiMQ4++GBe\neuklPv30U0aPHs2aNWs466yzmDBhAn/961+JeOLGwI033sidd97JSSedxFFHHQXAOeecw/r16/ng\ngw8YPny4P/biiy9m0qRJ3Hrrrfz0pz/t8twPPviAjz/+mD59+uyYjVp2CNYBYLFYdm+yOWny2hjX\n2XTXSK8f4fci1m7vnztOz/G+poAO6vb9Z5vSAi8NHdBtzWY9uZFmE5326uWVyRoAY7RHoNPMl0mb\nenxkL7np91qLYyEclX17pQLeXpTK2YMnXugG55OXkPnaWqFmPVQ2y1wAxoESdBfQQRTcExWMxIP9\npzuhvQWttUnuV74xTzYT1Oj70XMvwq9AZ4NneeR2QvAE+XLfbReCjADd3IDeuA4GVqG8M81m5Gx8\nIUjTCcLrFOHNYUostOv9POScY3FZkAURCsOWhCgtls3wP//zPyxbtowBAwYwcuRIvvWtb3HssccS\nCoU+/2bLV4ann36aTZs2UVZWRiwWY9q0aVxxxRXss88+X3iuW265hdtuu43TTjsNkAj/f/3XfzFr\n1qweY7/73e9y5513cvLJJwPw7rvv8otf/ILrr7/+X9vQV5gPPviAyy67jLvuuosJEybs7OV0IZmU\nIIWnJ/G73/2O9vZ2rrzyyh6lIjNnzuTOO+/kT3/6E0cddRSLFi3if//3f7nwwgspLy/vITI4ZswY\nnn322R4OgCuvvNIa/19B7G80Fotl9yaegJCDXi8K8OQXQixPovSmbl831UI2g4rlSV27NnXonsHn\ntdbzjGFPCd9xAsNUOaKyHwobYTn89njkijSFPEE/c027IiTnfYZoA6iCMtAueuWnYugWl0JCnAiq\nYpDZS4EfVZfIu4ZwLOcZnuPCiPG1t0o9u6dmD5JpYIxoTxNB9Rsk2Q2DhgSGurcnf934bQxVHiKU\nGI6KcwVEOwElY7zcey/DoahMOg5415wwdLSia9aJIV1s0lUzOV0GPAdENE80AQpKoXIveW4oHAgQ\nptrNOHmW2nOEjK8aLhoB3tpCETkD7516LQ1zz00ZochN1ej6jbKXjg6kI4TpGuCdibJCXJYvzooV\nK/jxj3/M2Wef7at7W/7v8dOf/pRJkyZxzTXXcPTRR39pB5DWmo8//pixY8f618aMGcNbb73VY2wm\nk2H+/PmMGTPGvzZ27Fg+/PDDL/Xs/ws0NjZyyimnMHXqVK699tqdvZwerF69GpDSHYBPP/0UgOnT\np2/2nurq6i5jH374YR5++OFex3qlJ7kMHTr0yy/YsstiHQAWi2U3RqGSJah0O+6SeQA4hxwvTgCl\nUMaAczeuErHA0n44nlBcTiRbtzfL3wvLkGhxTP5k02jP4HRCUg6Q6wDwnANOzj+lJs09qDl30Z0y\nh0oUGEX9GFRUQjaL+/qz6PpNOBOmoobvJ20NhxaZtaUklT4cwSkfJM6M3Ah2Nx0B3VyHXjJPxnnG\na2Gpny5PcwO4WdRe+8l8btYX9VNe+QP4z/DKH/yWe+lOKQsAVPlA6LencXB0yPx5SSmpiBcEkX8T\n5dc169Cfvgt5SZz9J8oa0x2mo0HEb8GoPAO9zyAoNzXRnpMg1QHtzfKOivvI+z/ocNSBE8T4j4jT\nQZUNDM7FOCx0JmVKHKLB+1IOOKA/W4Re9AHE4jBiH3AcnENPgEgyOA/rALB8CazAngWkj/y2IJvN\nkslkuqR6R6NROjo6eh3ruu5WjbUIy5YtY/ny5SxfvrzX7gtPPPEETzzxBFdeeSU/+9nPdvja3n//\nfSorK32jPC9PhGw/+OADDjjggC3e74299dZbueWWW7b6uVtsw2zZbbG/0VgsFovFYrFYLLs44XCY\nwYMHs3TpUv/a0qVLe43SxmIxBgwYwLJly/xrS5YssRHdLTB8+HBefvnlHn881f0jjjiCl19+mf/4\nj//YoevasGED5557Ltlslttuu82/7gko//a3v/3cOcaPH09RURGzZ8+mvb19u63Vsntg3ToWi2U3\nRkvUOxzG2fcwc82FdhHr0yZq6/SrkjR77aI3rZJosYkgyzQmgr5uOWCE6DwRP69lXHMdur0VlUhK\nlB4AE1322uCBpKi72qSuR0wGQJtEteOJQJXfzUotfP9KVGEhFJehvLZ0XmQ/V4Qw1QYoVCQuYnbZ\nrNThg6SqO2FUYTkMOwAyaXTtOtAaVTHY7EFDYbOk9Mfzg1R+o0uga9cFp+pIS0VZr5PTKUHJvSBn\n660zFJY9tbfIcyLxIB0/0ynrSBahRhwsY70IfIcnthgN3kGqTdaWzUjJQigs5QAgZ+mVazQZkcFY\nnonqh4LUfjdrMhBMFojW6LYmtJtF5YX8talYnggr7nMQup+IBFJQAFrjzn1FWj5GojB4T9i4ajM/\ngxaLxbLj8OrTx44dy6pVq5g9ezYvv/wyAIsXL+YXv/gF9913nz/2Bz/4Afvvvz/Lly/n6aef5u9/\n//vOXP4uTUFBAZMnT+5xfcmSJQD07du318+3FfX19Tz55JP+93V1dfzzn//k6aefprOzk7vvvpuZ\nM2f6n5900kmcdtpp/PjHPyadTjNz5kwGDx5Ma2sry5Yt409/+hNnnnkm48ePJ5lM8vOf/5zzzjuP\nqVOncsMNN3DAAQeglGLt2rW8+uqrRKNRrrnmmu22P8uug3UAWCyW3RatNR9/9CF9+/Wjcr+DReKv\nfr2kijthiIkAnCos91Xz9aZVYlgX9enRNk43bhJDtLBEDN1Ywjf2dToFHS3oSNRX2A/uzULWGMPp\nThHCC0chbB7gCdJpNygN8GrSi0shHhPHglevniNQqKIirqfbmuSCcUgo7frK9X6NfF4SFYtDZzu6\nqUYM74LSwGERS8jaHCcQNFSmQ0FrgzxXqa4aCE5IvipHHA0mzb5rS8GQtBlMd8i8oUiwl6zZZzyB\nKhRhPT8dP90ZODF0zvmlO6S8orNd5ikoCzQAvLKLDiN4FImCk9c1RV+blodeBwit5awyaRFr9BwF\nIbPGAVWoigHB/Nks2df+Ag01ZGJxVtZsYvWyJb3/EFosFssO5Nvf/jaxWIzzzz+fRCLB448/zqhR\no3ode+ONN/KTn/yEc889l2QyyZNPPsmIESN28Ip3fyKRCEOGDNliu8V/lSFDhgB0EWhMJBLsvffe\nfO973+OUU05h0KBBPe57/PHHGTduHI888ggPPPCAH0AoLCzk8MMPp7S01B97zjnnUFFRwZ133smM\nGTP8cpBwOMxBBx3E1Vdf7Y8tKChgyJAhfrtBy1cL6wCwWCy7LQpF/8FVIq7V2SYXw0b8DQWd8h83\n7UWmUx1iUIbC8neluhihXvs7GmvRG9ehSvrCIKkDV/GEGMKxRGCsekKCbc2+VoCKxsVobqoRp4ET\nEoE7hclC8Hrei5CfKq4wToOsOCBcF93SKHPlF0FpX1mnl4ngC9g5gZENYmgr5HmRqKzdM+j91nlh\ncMw1ryuBF8lPdcpePIFChTxTOaL2n+5A5SVFpA98fYPAi6LkM88p4HUoMHtDE2QFOCGTFVCC9lrt\nZTqDuZwwRJycjgSYtUUgr0D+7jkRshlxGIQioq3gnZFXv2nGKeWgQ0Ys0XtOujPQCXCzcj0Sg5CL\nGnEAtLUQjkToU9af4k/XwapANdlisVh2BkoprrrqKq666qoen40YMcKP/ntjr7322l1S0G53oqqq\nqkspxbYmFAp96fnD4TDf/va3+fa3v01bWxvr16+npKRks60ep0yZwpQpU8hkMlRXVxMKhejXr18P\nzYMZM2YwY8aML7Umy66PdQBYLJbdF6Xos8cwoiEHmmrRaEiWiOGYzYj6Pxqa68RQjMYhIQKBeMJ/\nmZSI9CmFGjBcMgWWL0B/+gEMHYXqv4c8qqBEjEzXRRuD2lO6dzesRNdVyxyVIyESQa9ciN64BvIL\nRVAOpO98OivryxPVezVgqESoa9bA+s9EaG+1+UVg0HBUaV9xFMS6eeG9LgdmD2RMurxXujBgWPCZ\nlykQjnbNRHAclBMG7eJ2tMn1WAKnpC+Av09du1ZU8kv6SjaFfBi0MjTrUHkFcn4drb5DRre3BO0B\nwxHZizk3XTYApU07vlbTZ9nLHnBCRsTRtG40XQlUUTlSslAtH6U75d3GEsG8Tgi0IyUDXqZAKCyZ\nG36pgA7W5pVvOCGIi1K7c/iJ/lGXKIeCj1fA3I82+6NosVgsFsvOJJFI+JkEn0c4HKaysnI7r8iy\nq2IdABaLZTfH1KeHQmLH+ZFpba5pE9WNBF+VuQ/E6PMMYy8tPhSGWJ4YrL7SfvA4PwrvpaOHQjIe\n0K1NqPY2iTTnF0rU3DNgvZR77/5cvO4CrgumXR+d7dDWLNFsU3vfRflfZ3OumfV3tkmHg1Av/7x7\nUXkvfT8UgYjynQFoiRj5rQG9aH4oIpkPua0Tc7sQ+BkG3jtwu17zSghcF5Qr+1KY9oXGwPei8V5S\ng1JBGj/dW2YpaSeoMXN3O89M2uwh56y80oxIPLg3k5ZSjFA4Z57cF23u7WwN3onFYrFYLBbLbox1\nAFgslt0bxxEDNb84MPQyYjiqZDEAqmyAn+quvYhzm6TZE89DxYxx3VIv9l9ZH4jsB0XlgdEciQIm\ngh2SudyNKwGps1dlA8HN4v7lUdzGOpyJJxI6ZAKgRbAPgvR5FMqk22lt0uGLyiFZjG6sRa9ZKZ+1\ntaI7m1F5BTijjxLxPzdjatVTIqIHxlkRRTfW4G5YCdEYzsDhJhXeGM9ai/5BJiXGsetKNkSx1DSq\nPHMGTghdv0HsX+MYUaX9UX0lE8LfS8bU1KMhI+UHmgK5v6PNr9FXpf3l/aQ75Vo2TbZ2HaAI7bmf\nnEmqg+yqRaBdeVf5RRKxD0dMSUMxvqNHi2GuivsaI95kAIRCORkL66C5FsIReS9a465dCql2VN89\nTBaDxq1ZA5m07C9ZLPN7+wuZ53W24y5+B129/dI/LZZ/lTfffJPHHnuMk046ieOPP35nL8disVgs\nuzC2DaDFYvnq0COyLsr1vop97p/cMd41rTFh8F7G9UZOFNyM125O9NuLfPdYZ6+LF2PbW4cvFuii\nvUh8l0ebtfoRa+96jjhfb/d0/+Nd77LXnM/8veXUzpPzWN3L+F725d+am6WRe0v3NXXf1+bm7fUw\nu8/VfX7v72xh3VuYy2LZxdi0aRPvvvsu1dXVO3spFovFYtnFsRkAFotl96a9BdyYUbrX6JZ6PyKs\nInExylsaxOBUjqSkK0cyBiDH8NV+2rgq6y+RaE8zAHCrl6MbNqKK+qD6VcmtJf3k1lBE6su1ixqx\nv6ypuEyi5QqUScfX6Q6/dt6rTVeF5ZKC7qXPRxOEzjaCTSGpg9dotKdZEI3nlCmILoDyShuKK1DJ\nEiMaaHLpO9v8mn+dSUE6hSrpJwKDOc4LZ+BwupRFoCWirkG31Em2QbpT6vsBVbGHiAUS3OZ1R1CF\nZVAgAkR+S8FonryPVAeqfr18lkmBI4J9zrAD5R3Ek6hITJweXimCJ+a4dhn6k3/K+OPPF52AWB6Q\nh25vQW+QzAmVl4TCMkh34q5ZLI6VflWocBhi+VIK4mbgjRfRdZtQhx8HI/aXd5AnbQD16oXoVAcq\nFMYZPAJVvgBYsPU/lxbLDsQKdn01aWlpobq6mrfeemu7PaOmpoby8vLtNv/uxMqVK3nrrbeYM2cO\nq1evpq6ujtbWVmKxGKWlpVRUVDBu3DgmTJjAqFGjegjnWSy7C9YBYLFYdm+8nu9KdYsuO0Fw2M3K\nH08AziFIjQe61Iqjg04BkVhXob2OVlH09wxnr5+8Xz+uIJ4HuKYTgZaUdSenntxbXyYdOB+8exUi\nzFfSp8sWlZtFtzbmrNUbb375MLoCKhwRpfsu9BL19/bmZgMdA6+9X3e0lrT4dKd0TuhsN2fqBkr7\nXfZBV/0BLxvCK0cIdTt37yyNhoKKxCR1382KE8Ar2QBxBDTWdn13uZoKXrmG45j9ubJupVCRqFwL\nR4zegYNuaYamBumA4P/MGIHAVKe0U4zEAmFFi8Vi2YGsW7eOt99+m1mzZm23Z6xZs4aRI0dut/l3\ndRobG3nsscd45JFHWLp0KQcffDDjxo3jxBNPpKysjGQySUdHB7W1tVRXV/Piiy9y++234zgOF1xw\nARdccAFVVVU7exsWyxfC/kZjsVh2c3KM6x7p8J5InZsjKNftMwClA7vaE+vbHL5Bqnpq0yEielo5\n+GJ4eCJ2uvvAz92ZeWDPbzd3a29p6l6Kvndjr2nz3b/XwS3eWre6LCLn/l7ZzBxeRwGvfKG3vXjt\n/Rynayq/d193wUbYvOgiBHPlnknWcyh9zr0Wi8Wyndlrr70YMGAA999//3Z7xmWXXbbd5t6VSafT\nPPjgg9x2221MmDCB7373uxx//PFEIpGtun/u3Ln8+te/5sADD+T888/nlltuobS0dDuv2mLZNlgH\ngMVi2b2J54Gj0OuXA9JbnngCMmn0miWARi+eB53tqMq9UKMPh2xaBPHQkkbudQbIywe/F7wRrmuu\nleeEQtIKsGYd7kdzJA196vkizJdJ+Yar2nN/SUZY8ynuqoUQy8MZekDXNTthVNkgABH1y6SCLIXc\nln+pDmlVp11pVYiWbAMnJGUHpjOAzqQk1d/Nilq9E/IFEN3GGrmmFKHKkbI3rwuCm+2ZMZDNoBs3\nyZhonqwnWQIFpZBJoUwJANEodJgOBbGkrKOzXdba2uC3AVR9BpvuAYg+QiiMGjTC7K9dsgramnHf\nfgVcF7XvoahBQ8UhkDVZEo6sUQ3cE9VXzo3GGtmf96x0yi9PIBxBRSIQCuHs+zW55pVChKMmw8NF\nHTQeWhtRQ/dGlfVHN9SQffQH4IQITb8YVVwG2Sy6uS5wUFgsFotlt2bNmjVMnz6daDTKCy+8wMEH\nH/yF5zj00EM59NBDmTVrFjfccAP77LMPTz75JBMnTtwOK7ZYti22eMVisXxF6C3qHAjpSes73fOz\nLpHkrYj2ehkArmk12B1PMM/LANicIF+PaPrmQuabEfvb3NAtzaE2lwHQy/juEfjcNP8umRS93f45\nwnm+6GLOeO8ddVUX7DZ/TgYAOe/NL/vIeZ/+Ld2EGHPXbvQHemQAuFmbAWCxWCxfQT755BMOOeQQ\njjnmGN58880exv+mTZtQRpC3tz9tbW1dxg8cOJDf/va3/PznP2fatGk88cQTX2pd4XDYf0YkEqG0\ntJQBAwYwefJkbr75Zj755JMvvWeLpTs2A8BisezeaA2pTvRniwBQ+00wQnlBqrgacaDYv4mkCPSh\nUYkCsRNDYT9CTTYdzKm1aUEXk2vRPDEM+1fh9NszqGn3DES/3CADKFRhaVBz7s3vjc1m0BtXyW0p\nIwyY6pB6/Ggeas99g/FOCLSD8uaIxFEhERzUqfbgHJQDHY3omrWAMuJ7SBu+/CKkZMH8k+9mpR2i\nlzkA6HRn8JnRBVC0yxpiCandD0WCVoahsKzNzaLrqs17aBcjPr9Q2vQBeskHsreSCtSAIXJvOIov\nSphNS3bF/ofJu+ozQJ7RWIOuXi7nUTVK1tFSj960Rmr6ywfIORdXyGe5egaZtLQyDEdQ0bi8Z3OO\nfqcFx0ENHilZHtpFr/8Mslmcw6f5Ioo61QHpDhEXbKrd2p9Ii8ViseyCNDY2MmPGDG688Ub+4z/+\nY4tjp02bxhVXXNHjeiwW63X8KaecwqBBgzjuuOMYPnw4Y8aM+cLrq6qq4qGHHgKgvr6e+vp63nvv\nPR555BHuvPNOvvnNb/KjH/1I/htmsfwLWAeAxWLZbdFa8/H8BfRNROm/aZ1poYcYqjk1/6rvHmKI\nZ9OQ7hDHQFzS1sUBYP6D3maE9vz2cMoX+iMShWwMlcgxbjPdHAYQpIrH81HRPJOub/6p9SLRXlq5\n1ugOk5puVPbJS+bs0BP60/4cKhSWv2dSgehdSITtdLoT3VgjazEGvepbFcxpnq+9LIZMWoxzCIT2\ndE4bw2xK1hCN40ffw+Y8HNNNwc1Ca0OXvahksd89QW9YBS0NKDcL/faQdxKKGnHBjKwhFEZVDpNn\nGAFGnU6h6zZAokCcH46D9s5NKVSfQfI1USAOg5x3oDeuhNamQAgQ/KwD5QsnKlRZfzH+66qhcRNE\n4+IsAnGMZNNkOtpZvnA+q1et7O1H0GKxWCw7mEmTJhGPx7nuuus48sgjt1qN/1vf+haHHXbY5xr/\nAJWVlUyePPkLreuQQw7h3nvv5eyzz2bBggVfuEtAMpns9Zn33HMPZ5xxBvfccw99+/bl29/+dpfP\ntdbMmzePZcuWATB8+HAOOOCAXh0FWmveeecdVq5cSSQS4cgjj6SgoIB58+ZRXl7OHnvs8YXWbNk9\nsQ4Ai8Wy26IU9O9bQUEkhDNwiB+5BSXG5YY1YhQWVUDYRKw9Y7G9WTLI21uhoV4MwiF7m2hyJsgG\n8JwIThgdjQcGMEjEG4JOBLk4YYiEZS3GUaBbGsxYjSowYkF5BXJvOuW3vXMXz5NnJougvJ/JRjDG\n+8rFMl8iCcWmDV+mzS9xUMUVQUq8t37XtNMLhfBF+BzHdAMw6v9e20CvXaIG2pukZWFjHaTSkCxE\nlVXIuNr16LZWCDmQFGOfjrYetfKqz0AoKIbiPl0yENDaaC2EAmeC0SVAuxK57zvY6BCYueIJKB8o\n4yJxUKCb6yG1XhwEnnGfSYvTIhQWp442GQ7aNSn+xjlUUiFaColCcaKEI34JgW5rgmwaJ5OhT9VQ\niiuWwWc1m/1ZtFgslh3Fo48+yosvvkhdXR2DBw/muuuuY9iwYZsd/9prr/HQQw9RU1ND//79ufji\ni/na1762A1e8bbn++us5/fTTOfXUUykuLmbq1Klcc801jBgxYrP3rFmzhtmzZ/tG8uehtWbNmjUA\n9O/fn1CoF9XfXrjgggv4+c9/ztNPP80geR37AAAgAElEQVSpp566Vfd8HgUFBTzyyCNUVVVx1113\nce211/rrWbJkCWeeeSbvv/8+ffr0QWtNTU0NhxxyCI8//jhDhgzx59m0aROnnHIKb775JlVVVeTl\n5VFdXc2tt97K1VdfzYUXXuhnIFi+2lgNAIvFshujKC8ppqC0DDXqENQ+40QAUClIpdBLPkF/+pEY\n6lqLkZcohGgc3ViDbtyEXvYx7mtP4f7tGVQkLgJ82bQYjh0tEklPd0o6eaIwSIHXGtqaZFxnq0TS\nUx0SOe5sM+J4CTFyTfs8vXYJeuUC9MZVqD6DUBWDcQYOwxm0F86e++IMG40qH4T7xp9w3/gTetnH\nqFhC1mT+uO//Dfd/n0N/Os+vm9ctDej69eIA6D8ENXAYqmoUqmqUrMNkC2itJfqvHOOgiEl2QF5S\nMhsShahEESpZikqWoDvb0a2N6IXv4b71AvrTD6RlXqoT/dkC9Puvoxe9hyooRRWaPtLZDErroGZy\nyL6okQehBg5FhaOSwZBJy7h4vjwvr0CcAI4jZ9/ZLpH/YQdKmj5Kzju/GLXHKNQe+8i640n0xtW4\ni9/BXfI+euV89Mr58r4TBRCJoes3oBvWo9d/hq5ejrv0A9z5c3AXzBVnQCSGKumH6rcnqnygyYBw\n0fXrpZyitYGSvfanYKCNilgslp3PQw89xMyZM1m6dCnjx4/nj3/8IwceeCCfffZZr+NfeOEFpkyZ\nwsKFCzn11FNZsmQJkyZN4q9//esOXvm247jjjqN///40NDSwYsUKHnzwQSZNmsSoUaO45557qKur\n63HPs88+y7HHHkufPn16mbEnP//5z6msrKSyspJEIsHEiRN56aWXturemTNnfmktgM3Rr18/xo8f\nT21tLQsWLACgqamJo48+muXLl/Pqq6+yceNGNm3axP/8z/+wYMECJk+e3EWz4PTTT2fu3Lk888wz\nLF++nPnz5zNnzhx++tOfbtO1WnZ9rAPAYrFYLBaLxWLZDbjtttsA+O///m9uueUWLr/8clpaWrjv\nvvt6HT979mxc1+Ub3/gGl1xyCZdffjmu63L77bfvyGVvc/bdd98u32/YsIEFCxZw4403sv/++zNx\n4kSeeeYZ0mnJwFu0aNFW1eXHYjFuvvlm3njjDZYsWcJ7773Hfffdx4oVKzjuuON47rnnPneOsWPH\nsnDhwi+3sS3Qv39/QCL5AI8//jirV69m1qxZHHXUUf64Y489lhtuuIHPPvuM2bNnA/DRRx/xt7/9\njZkzZzJt2jR/7IgRI7jrrru2+Votuza2BMBisezeeEr7Xq2bEbXDUaixk6Q23c1CSz0qmpBIczYj\n0V80qt9gacmnFFpnIatBhUQXIBQKBPxSHejOFCoaD1LN84vkazZt5kNS15UjKfXKkRaF0ZiIEJYP\ngEwG5ZUpaBf3w39AewtqyCjoM0DS32MmLT8UlrWnU+gNn0mEf99DwNUyrxESJFEoEfhwVNLYlfJF\nA/02f1rLeK/uP5uBzg4RRVQODNvPV+bXpvxBFZlISSQh64tEJeUeoH8VqqJSSis6RSxQFVdIVkIk\nFugjhKNg2i1qrSUTYuE7RqcgJV/j+ah9DzXn5qDCGp1bupjNEfczZRcqLwkYLYCCYslo8MozIjFU\nOCxzR+Py/GierK24b1ACEI6AmxGxv2zaCBNKuYTKL4aEjNOtjcHPlcVisewkmpub/bR0r1a7qqoK\nwI8Kd8crDXjuuecYP348Tz/9NACLFy/2xyxfvpzTTz99ey17u7A5AzudTrN27VrWrl3L3LlzKSws\n5LzzzqOuro799tvvc+ctLCzs4RwZM2YMRxxxBPvvvz833XQT//Zv/7bFOcrKyqit3fbCsU1NTYCU\nBIAY9QBHHHFEj7HetQ8//BCA+fPnA9K+sDvjx4/f1ku17OJYB4DFYtm98RwAjqnPS3eK4acUag+p\nB9R16yHdiVYOyk2Kse61jSssQ1UMlnuzadBZI1RnxPaMCKB2W4M5IqamPpaQr6l2IB1cc3JqBRX+\nHCpZIjXuTkiuuxq9+lNorIWyfqgyU+/vC+05YqxmUuj6jaBdnKEHQixPUtvXLpF58wslJd5xgs4E\nOYa/d066qU4M2fYWcQK0t0FTvRjeA/Ywtf9GnE8pKBsopQ/5xXJeLQ0imAeosgGQLDYigCKeqBIF\nMkc4EggJ5uoOgDgzqj+TfXWYDggFJaj9xosyv5KzU64rzg90MFe6U7QbUBDLk68FJdJxwTFlDSAl\nD949pouDCkXkWeFo8H6ckKwjbco3tPb1GlTcnKebFe2GdOrzfhItlp3GG2+8we9+9zumTZvGiSee\nuLOXY9lOxGIxwuEwmUzGj2ynUvJvUzKZ7PWe6667jk2bNvHUU09xzDHH+HXy5eXl/piSkpLdThOg\npaWFRYsWbfbzWCxGQUEB48aN46yzzuLPf/7zZssktoZRo0YxbNgwFixYgOu6WxT4W7ZsGUOHDv3S\nz+qNjo4O5s6dSywWY5999gGMoC/SQrA73vq8MZ4gYNYEK3Jxu2n3WL76WAeAxWLZvfEE5LIZ/P7v\n3XvdG6NPhSJBe0DTig5HBWr63tdsJnAQeGQz8nkobCLIBIYymJ7xBM81on7aizSDL+SX6yBQ+UWm\nLl9JdDybgsIS+TAvH199PybihTrdiULLGjwHRChiovfaRMtVIAIYjvnnoSIxtHZ9sUE0YvAqcx6e\nA8AxgnydbZAO+cr8hCMmom7ua2s2zzfR9rZmyU7ILzQGunceOa0SlekqoF2/+4LKLwyEC70j1wR7\n8oz5nG4IMk7ntGGk6/vyD9hT/QdJK8hxRqDlPtecp3euisCZ4nUmcOx/Li27LnV1dXzyySdMmDBh\nZy/Fsh2JRqMcfPDBzJkzhzlz5nDyySczd+5cAA477DBABP9eeukljjjiCKZOnUo4HOYnP/mJX+d9\nxx13MHfu3C5R45KSEs4888wdvp9/hf/+7//ucS0ejzNw4ED22GMPLr/8ck488US/bd+qVau45557\nvvTzWltbWbNmDRUVFZ+r7v/6668zevToL/2s3rjjjjuora3lG9/4Bvn5+QC+I+Cdd97pkd0wZ84c\nQBwXgF/+8Oabb3LRRRd1Gfv3v/99m67Vsutjf6OxWCy7NSqeFKH7DZ+JPZirNm9wKvYIjG+QqLAX\n9U+1o2tWy99bvEh2IcTiojTvGe+NNej6DaLe77UG9AzJvCTE883D5Jq7frlEy2MJnL0ONuMK/CVI\nl0EHdfh0FBq9bgnu0vchlocz9VwzvzFCQ0mc4WNl3kX/RHe0oUr74Yw4yDsF+dLRgm6qkah1q6QK\nOnvuZ5T0FQwahtJaMgDSnYgBbLIlTBmEj+uSfe9laGvGGXEQql8VxPIkzR9w589Br10K+YU4B08F\nNO6Lj0FTHerAw1GD95KVRUzE3c1KaYHjoIbKLy2q/zB5F1pDRtoW6mzGLyNQ8XzIptGmzSDReFCW\nkOo0WzdOHTfXsWGcN8oRUUgwkf2svE/vnZpsEZ1qlw4GXvtEpVDllcZRoaXUw+vaYLHsgkyfPp3p\n06fv7GVYdgD33nsvU6ZM4bzzzmPWrFnMnz+fgw8+2O9Z/49//IMf/vCHKKWYOnUqK1as4Mgjj2Sv\nvfaiurqa+fPnM378eH7wgx/s5J18edrb21m5UlqzKqXo378/5eXlnHfeeVxwwQWUlZX1uGfatGlc\nc801zJkzZ4sp76+//jp77LFHF/X8lStXcskll9DW1tajBV93Wltb+dWvfsUbb7zxJXcXUF9fz9tv\nv80vfvELnnnmGcaNG8e9997rf37OOedw2223ccsttzBhwgRGjhwJwMcff8xdd91Fv379OOOMMwDY\na6+9OPnkk3nssceYMGECF1xwAZFIhDfeeINZs2b9y2u17F5YB4DFYvmKoED1EgHOxesVn9uyT+NH\nnnUm43+vlOqSROD1ke9yLffZufMpb7zT1ajOjVBrE9V2MybKnbv2nDB496i2coJ5vc+8zAN/f+Q8\nt5cFd8+QAGM8m/05IUCjVE5rve5r621/XnYF3c64+7N76U3c9RE5+9bdrrvZrtF+r54/972aVn5d\n0wm6/+m2Je/+TCZwKHhZAbqXeywWi2UnMH78eJYtW8brr7/OunXr2GeffZgyZYrfFu6UU05h5MiR\nvjE4cOBA7rvvPpYuXUp+fj777bcfhx9+eK894ncXvve971FbW8uIESM45phjuPLKKxk+fPgW74lG\no9x8881ceOGF/POf/9xsycTDDz/M448/TmlpKcXFxXR0dLBx40aUUlx55ZV897vf3eJzLr30UqZM\nmeJH3r8In3zySY/3EolEGDt2LPfffz+XXHIJkUjQiri0tJTnnnuOU089lTFjxrD//vujtebDDz+k\nb9++PPXUUxQWFvrjf/Ob33D55Zdz2WWXccUVVxCJRP5/e/cdXVWRxwH8e196750k9FBCKCGUQBIg\nVJVeBOkICKy72GEBFRELSBFFWEAQEHZBiAiLlERgAUE6BEF6gPTe+yuzf9zkhmdC04Qk5vs5J4d9\n8+bOzL3JOev87sxvYGNjgyVLlmDMmDEwNjZ+6jFT7cQAABHVfgYGkKwdyiaIupLJbMmybaEpliem\naQnQ3b8GydQcUrMAQFJBJMdCXDkFodXh1893QGh18H7nNTj06y0fB1eaEM/eVd7DX3pcHSAfKYiS\n/eUGBmUJ9IQOkqMnJAcPuZ6mSP4uK1meYBYVyEfq6XRAciKEWg2pYVPAyUWeZ5Ym2hNCXrIvGcir\nEiRA1dBPXs2uLoLISJL7t7IDTC0gCvMh4u8CxqZQeTeXE9iVLs8Hyia6phaAqaU84dVpAa0GRZ+8\nA2i1kOwdYDT2FbndBi3l7QamVhDqIjlIoJbfvEtOHpBsHeXVFlo1AAHJr7O8TSI/G7qbFwEAqmYl\nRzOWvpE3NIHkJv+HmmRkIq+YECjJFQDoku5DZKeVPWudRpl7i+ib0F27KL+hb9lO/j0U5AHFxVCW\n76Mk2aKlDWBgJCdDFEJOXqhVy0cqGhnLbVjIyQNFwl2I1Fjo0rOQvzUMMFDBfMxwqOxt5WMLbZyA\njMRK+3MlIvozXFxcHrpkv0WLFsrScEDeCz906NBnNbRnwt7eHvv370eXLl2eKpAxffp0HD16FCNH\njsT27duVpfQP2rBhA1599VX89ttvSE1Nhbm5OerXr4+OHTvC2dn5oW0LITB//nycPXsWZ86ceep7\nOnPmjLJfv5SZmRkaN278yIl5586dcffuXRw/fhxXrlwBAHz66afo2rWrXrAAkJMHfvvtt1i2bBmi\no6NhaGgIX19fnDx5EkBZQkn662MAgIj+Gkr31WuLH3hrrv8mXajlyamAgFS6F1yrkSeRWi0KYhIg\ntFpo8otKlvmrgdLt5wZGgLGk325pn1LJnnkJZcvPDY3k70uXt5cmmCvNwp+dIS+LT08G1GrAwwvK\nW/kHl7LrdIBKB0AHCAmSidkDS95LEg+KkmUHOq08QTcwAIyMyr+hV97eG5QlGATkZIRJcXJwQqsu\n69/UXG7DoOQ+Hlxmb2gkT/4lVVm7ZhaAzlTeflCaNV+n1V/FIElKYj4lkPJg7oSSUw+gUT+Qh6Hk\n+uIiOWGipJIT90kqoDBPPs3gwVUDxYWA1uKBlQFCCXRApwF0pYkJVUqiP6iLgaICaBMT5fvNzQJM\nDSAMjSCZWcnPhoiIqt0777zzh6/dsGEDxo0bh65du2LHjh3KKQmlTExM0Llz56fKjJ+dnY1p06bh\n119/xYEDB/Teuj+pJzmi8GGMjY0RGhqK0NDQR9bLy8tDbm4uXFxc4OQkb6dLTU3F7NmzYWRkhCFD\nhvzhMVDtwgAAEdViArrkGAijkuPygJKM8CWZ8JXEbfLybsncCqjXRD6SLj0BgARkpkLk5wJCoEGP\nloAQsLLUQiTelRPZWdjKTegKIDTF8tt+Y3nfurh2Rv7XwVVOZIeykINkaiHnEFAXKdn6RUFO2Vvq\nJq3kialbffnNu6sXYGsvT85LJsgiOx0i6b781trSVp7jXzou71fPzoRIjJPreXhDsnMoWX0gBxpE\nSpz8ltvJUznKUDIwBCDJKyLUWkBTBFGYD+i0MPBpAuh0kCxt5GPvSgMKKhUkC1tIhqby24nSSbuB\nsfKcJUMTAEJOeAhA5ewJuJTkWDAwkFcFSJJyBKPIKTkeycRcbk9SASYWJc/NErADIHQQqbHyGEqT\nDVraQBUyEBACuhvnASEg2TkCVnYlpxrkyc8jMwXIzZKPZDS3ArQ65O0Igy4tDWbPvQAjv9ZyvZIg\nhWRtDxiZQOVUDPPXHSFJElRNG0AyLUkeaWELyab8nlIiIqpdzM3NsWPHDnz88cdo3749pk2bhtmz\nZ8PW1vap21Kr1di0aRPmzZuH7t274+TJk8oRfTXRvXv34Ofnh5YtW8LFxQX5+fn49ddfYWxsjE2b\nNlX6yQVUczEAQES1lxBIjY6CtaUFLK0sSyaZzvISbzxwFJ665A2xiSkkexd5EpqVDkBA5OcoCeWc\nmstL9iUTHURWCmBlLyf9g7y8D1oNhIGhHATQ6ZTj7CSVquzc+pJJNoxMAEOdPBkvWapfetY8jEwA\nt4by5NlePgpPsrQry+pfuu9eXQSkJ0GYW8nJ+yQJIvqmvEUgPR0iJlquXpAD4ewCmJkD1rbyOHMz\nAEiQbF3KVgEYlWT6Ly6UJ+VFhfKxekIHlaur/Mbd1AwoKii5l5KVAuZCngirHsgJYGhUdvqAgZGS\nTBCAfLSimby/UhTmyG/dVQaAKHnbnptRtudeZSD/GJnIz83YBJJKgsjPgchOkQMmBbnyfTp6QFXf\nF9Bqoftlv3yco7Vd2RaDkgAA8nLk1RWmFpCKCyE0GhSfOQdNXByMAzrDqHQFQmGu3L6pBSQzS0gq\nFUwalezb1Mq5GQSArEI1crS1d78sERGVkSQJc+fOxejRozFnzhx4eXlhwIABGDVqFDp37gx7+4cn\nfS0oKMDFixcRFhaGLVu2oHHjxti5c2etOEaxWbNmuHjxIi5cuKAcH+nt7Y3g4GCYmZk95mr6K2EA\ngIhqt9Kkclqt/K9OA2hLVgAoR8aVLF9XlqJL0EtmV5L0Tq4v9JfOax84gk45ck6U1VOVNifK/i2t\nUy55nFSWILCUTlsytoqS5v3+yDpRdjydSqXsm1c+l75NV6kAlBxLqLcDQADQ6TWvUKkAIckrEMou\neODngecIQKg1ch5DlQQDyUD/eT6YBFDZhVHBcxAP3Ffpc9bpyj83JRGhVPadSs65oHfMX+mzKk1E\nqHrg96WS5J/fJ2UUOv32S5WMQwBlvyMiIvrLqF+/Pv79738jISEBmzdvxoIFC3Dx4kXUr18fDRs2\nhIODAywtLVFYWIi0tDQkJCTg119/RaNGjdC3b18cOnQIvr6+1X0bT8zAwAB+fn7w8/Or7qFQNWMA\ngIhqL0kFu+btIKWnQLdtFYROC8ndAzAygmRjD9Xz4+Tl/tfOQBTkQrJzgeTZWN7vXbI3XXKvD1WD\nFlDe2gPyxNpABREbBe3RvShQa2DRuRek+s0gctKhi74GQILKP1Sek2amyMvOAflttU4H2DnLSQI1\nJX1JEiS3BnJSOkBeLq/VQrt7O3JTU2D93DCofP3lyahRScIfCyvA0R1QqaCLvyPfcrtukFQGEPnZ\nkDKS5XpO9SBZlyTNMzSWJ7VFBQAEYGKBgqJiGBkawuD+VYjiIkgObnICPE1JYj8JUIUMkp+BrmyJ\nvsjPKUkaaAkYmkAk3IO4cR4A8Ovek4i9dBuWLg7o+NZ4qAwNYdysPSQTc+jib0OXKY9N5eIt34/K\nEDAq2f7g4AFAyNswNGogLxfi1P8gdDpILdrI+RCKC+Wl/yZm0Db2h1qjgbmBgC7+FgAJBi9MACBB\n5KRCFOQClrbyUn4Akq0LJHMbCK0aIi0e0Glh1b4JRBMnGLrZy/cpdBBRVyAK86DzagG1rQvMTUzk\nbQFCB3H5BERBHqDTwaowHxZRkZX/90tE9AixsbEICwvDd999V2V95OTk4LXXXquy9msDNzc3zJo1\nC7NmzUJBQQHOnTuHmJgYpKenIy8vDyYmJrC3t4ezszMCAgIqPGaQqDZhAICIarXswmKkx8SiaWaa\n/BbZzBgwMoKAVPbiujBPnkxa2kA5Rq/0zbaRMVAycYRpSUZgTbE8MdZooE1Pwd2UDPi2V5csdYc8\nOZUkeX+5JAHZaWXJ8YqLypLxaUqS2ZWQjEweOPdeXn6nzczAb3fuoVNRUdlNKW+yDeSl9pJUln3f\nwRIwMoFkaAAhSvMe2JXkCChZHaDTyj8AIKlwNzoGLk6OsCsulAMDpasllNfwUsn1kjyu3HT52tIE\nfqUrFDRFQF42AKAgLh7Zt6OAglxkpSRBZWwM59LxatTKsn1otYCBDpAeSNJnaKSfmK+4CCItqWy5\nv6YkEWFJ/9nFWiSlpKJFPRf5OUgSYO0t/1uUKycCNDBQch3AzBKwtJGX/5e8vVeZmwI6M0hGZf+3\nJ4oKgcJ8ZGVmIjlbjRY+TZTEi6IgV75XnRbIzSm7HyKiZ8TDwwNjx47FkiVLqqyP119/XTlCkOTM\n+0FBQdU9DKIqxQAAEdVaGo0Gb86ei6KsTNjG3ZYnleZ35cR1JqaQfrkn75tPjpEnlWYW8pF5Qicn\n/oMADI3lZHFA2f59IU88RXYGdEmxyCwogv2tTEg2DhDFhUC+PAmWrOW3AKIgVw4KAPIEWgg5gWDp\n2/jCfHmubW4DqSSJniiZaOpuXkVKZjZcvlwPyXGv3H/Jf4yJ4sKyiWdpUMDcWt6LX3qaAACYmsuJ\n+JRs+qIs8GBgiPTMLJibmcGkOE+eWJtZQjI2LWlD3u8vlRxpCFEy+QXKAgCmFpCMTCDys4F0+c1+\nyp045BTlwTgxEQ5rtkEyUMHs+6OAgRFETro8KQcAC1v5nku3LqBsjKIgtyRYooaIuy+vyDgbDVhZ\ny+UaDWBoiCJTG+QXFsLO0lw5XUAyt5F/VQW5ZUGBku0Lkqm5HGjRaSFyM+UuE2Ig1MWQzsZBspWP\njBTpiYBGjSJTK+TDEPa2NkqeBpESV3ISgfwsbyamwchTP1s0EVFVkiQJxsbGVZpY7vdHxRHRXx8D\nAERUa33xxRfQPNHxbAFVPpY/LLhndY+AnkAboNxxUURE9NeUl5eHb7/9Fvv370d+vhx49vX1xZQp\nU9CiRYtK7Ss5ORnvvvvuQ78PDQ3FiBEjKrVPqtsYACCiWmvatGnVPQQiomp39OhRbNy4EYMHD8aA\nAQOqezhEtdrVq1fRr18/pKeno0ePHvDz80NxcTEuXLiAiIiISg8AZGVlYe3atahXrx46d+5c7vvS\nAARRZWEAgIiIiKgWy8rKwu3bt5GRkVHdQyGq1dLS0tC3b18YGBjg+vXrqFev3jPru1OnTlWa8JGo\nlOrxVYiIiIiophowYACOHz+O8ePHV/dQ6BkpLCyEVjmm9vF1dTzK9ImsWrUKsbGx+Oyzz57p5P9x\ndDod2rdvj3nz5mH37t0IDAyEvb293mqEHTt2IDg4GI6OjrC3t4efnx8+/fRTFD2YZLhEeHg4unbt\nCnt7ezg6OuK5557D5cuX0bdvX7zyyivP8taoGnAFABERERFRLZCYmIhJkyZBCIHMzEyEhITg448/\nhkpV/p1efHw8Jk2aBEmSkJGRgZ49e+LDDz+EVJpUlsrZt28fJElCu3btMGfOHJw7dw6Wlpbw8fHB\nuHHj0Lx582oZlxAC58+fR2pqKjZu3IjZs2ejadOmyvaAuXPn4uOPP0afPn2wYcMGWFlZYfv27Zgz\nZw7279+PQ4cOwdBQnvbt3LkTI0eOhL+/PzZv3gwHBwecOHEC/fr1Q1ZWVoUBA/prYQCAiIiIiKgW\neOedd9C6dWt88sknUKvV6NixI9q3b49hw4aVq/vGG2+gY8eO+OCDD1BUVISAgAB06NCBeSIe4f79\n+zAzM0O3bt3g6emJXr16ITc3F5s2bcKSJUuwceNGjB49ukr63rlzZ7ngjIGBgV6y46SkJPz66696\nSWnv3LmDRYsWITAwEPv371fa6N69OywtLbF06VJs2bIFEyZMgE6nw8yZM+Hi4oLDhw/DwkI+/rhz\n586ws7PD5MmTq+TeqGbhFgAiIiIiolpg3759GD58OAD5CL9Bgwbhxx9/fGxdExMTDBw48KF1SabR\naJCfn4/AwECcPHkSH3zwAZYuXYorV67AwcEB06dPR3Z2dpX0HRQUhIiICL2fgwcP6tXp2LFjuRNp\nDh06BK1Wi4kTJ5YLIJQu5y9t58aNG4iPj8egQYOUyX+p0aNHV7iShP56uAKAiIiIiKiG02g0SEtL\ng5OTk1Lm5OSEX375pVzd/Px85OTkwNHRUa/u5cuXn8lYaysnJyekpKRgwoQJeuX29vYYNGgQ1qxZ\ng7NnzyI0NLTS+3ZxcUHPno8+Gtjd3b1cWWnyTzc3t4fWT0tLAyAnDAWg93dRytTUFJaWlk83aKqV\nGOYhIiIiIqrhDA0NYWdnh8zMTKUsMzNTLyBQytzcHBYWFsqE71F1qYy/vz8Aeen975WWVWdCxYry\nN7i4uAAA7t27V+67u3fvAigLDnh5eQEAbt68Wa5uQkJCla1uoJqFAQAiIiIiolqgZ8+e2L17NwB5\nIrp371707t0bAJCTk4PIyMgK62q1Wr26VLGJEycCALZt26ZXnpubiz179sDc3BwBAQHVMbSH6tOn\nD0xNTbF69WoUFxfrfbdixQoAwMCBAwHIKwKCgoIQFhaG8+fPK/V0Oh3mzp377AZN1YpbAIiIiIiI\naoHPPvsMAwYMwOXLlxEbG4vGjRtj1KhRAIBz585h2LBhynLvZcuWYeDAgTh//jzu37+PVq1aVZgs\nkMp0794db7zxBpYtW4bc3FyEhISguLgYX3/9NeLj47Fu3TrY2tpW9zD1uLm5YdmyZfjb3/6GLl26\nYPLkyTAzM8OPP/6I7777DiNHjlC+CiwAACAASURBVMTgwYOV+uvWrUPPnj0RFBSE4cOHw8HBASdP\nnoSxsTEcHBx4SkQdwAAAEREREVEt4O3tjcjISMTHx8Pc3FxvMtq9e3dl8g8ADRs2xK+//oq4uDhY\nWlrCxsamOoZc6yxZsgSdO3fG5s2b8eWXX8LCwgJt27bF2rVr0aVLl0rvz8bGBlOnTkW7du0eWkeS\nJEydOhUdOnSo8Pvp06ejRYsW2LBhA1atWoXi4mL4+Phg48aNGDt2rN6k3sfHB1evXsU333yD3377\nDQUFBXjllVcwfPhw2NnZwcHBodLvkWoWBgCIiIiIiGqRipLBPYyHh0cVjuSvR5IkDBs27JmtlnB2\ndsaaNWseWUelUj22TkhICEJCQp6oT2tra8ycOVOv7Ouvv4ZGo0FwcPATtUG1FwMAREREREREdUBR\nURFCQ0MxZMgQeHh4ICcnB8ePH8fWrVvh5+eHSZMmVfcQqYoxAEBERERUg2RnZyMmJqZcIrLKFBUV\nBV9f3yprn4hqJkNDQ3Ts2BG7d+9GXl4eAMDV1RWff/45Xn75ZZiZmVXzCKmqMQBAREREVIPk5uYi\nOTkZ4eHhVdZHbGwsAwBEdZCBgQGWLl1a3cOgasQAABEREVEN4u7uDn9/f2zYsKHK+pg2bVqVtU2V\nIy0tDdeuXcOyZcuqrI+rV68+8b5xIvprYACAiIiIiKiG0Wq1KCwsRHp6epX1UVRUVGVtE1HNxAAA\nEREREVEN4+zsjE6dOmHhwoVV1seDxwYSUd2gqu4BEBEREREREVHVYwCAiIiIiIjqvEmTJkGSpIf+\nGBsbV3qfOTk5kCQJQUFBD60zZswYSJKEq1evVnr/VPdwCwAREREREdV506dPR79+/cqVnz59GkuX\nLsWoUaOqYVRElYsBACIiIiIiqvMCAgIQEBBQrnzTpk2QJAlvvfVWNYzq0YqLi3Hp0iXExMTAyckJ\nbdu2hZWVlV4djUaD6Oho2NjYwMHBAXfu3MGVK1fg5OSEwMBApZ0LFy4gPj4ehoaGcHV1RevWrWFi\nYlKuz9TUVERGRiI9PR0eHh7o1KkTVCouLK8tGAAgIiIiIqolEhMTcfbsWZibmyMwMBBmZmYPrZuQ\nkICzZ8/CwsICXbp0gamp6TMc6V/DlStXsG/fPvTt2xetWrWq7uHoWb9+PWbNmoXMzEx4eHggKSkJ\nkiRh5syZ+Pjjj5VJeUJCAho1aoQpU6YgNjYW+/fvh62tLVq1aoVjx44hLCwM06dPR05ODtzd3aFW\nq5GSkgJLS0ukpKQo/WVlZeEf//gHtm7dCmNjYzg6OiI2NhYNGzbE119/jW7dulXTk6CnwVANERER\nEVEtcPbsWQQGBuLq1avYtWsXunbtipycnArr/vLLL+jSpQuuXbuGnTt3Ijg4GHl5ec94xLXfZ599\nBiEE3n777SrtJzExEWvXrq3w59atW+Xq7927F1OmTEHbtm2RlJSE+/fvIzs7GxMnTsSiRYvw0Ucf\nlbtmw4YNaN68OTIyMpCRkYEDBw5ArVZj/PjxaNeuHZKSknDnzh1ER0cjMzMT27ZtU67V6XTo378/\nvv/+e2zbtg25ubmIjo5GbGwsGjRogOeff77CcVLNwxUARERERES1wD//+U/MmTMHkydPBgAMHz4c\na9asqXBp+qxZs/D+++9j/PjxAIBBgwbh66+/xsyZM5/pmGuz2NhY/Oc//0FAQAC6d+9epX3du3cP\ns2fPrvC7igI3n3zyCUxNTbFlyxY4ODgAAIyNjbFixQqEh4fjs88+w6xZs/QSF/r5+WHJkiWQJAkA\nYG5ujoyMDOTl5cHGxkavromJCUJDQ5XPe/bswfHjx7Fs2TIMGzZMKXd3d8f69evh7e2NNWvWYMmS\nJX/uQVCVYwCAiIiIiKgWOHPmDL744gvlc5cuXXDixIly9YQQOHv2LDZs2KBX9/Tp089knH8Vy5cv\nh1qtrvK3/wDQqVMnHD9+vMLvxowZg61bt+qVXbhwAc2aNYOLi4teuZGREYKDg/HNN9/g5s2b8PX1\nVb4LCAhQJv+l7Ozs8Nprr2HFihX48ccf0atXL4SEhCAwMBAdOnRQ6p08eRIA8N///he//PJLuTEa\nGhri5s2bT3fTVC0YACAiIiIiquF0Oh3y8/P19vybmZkhNze3XF21Wo2ioiK9Pf9mZmYP3S5A5WVm\nZmLdunVo1KgRhgwZUt3D0SOEgFarfeixhKWJ+7RarV7575MDllq+fDmmTp2K8PBwnDhxAkuXLsXr\nr7+Onj17Yvfu3TA3N0dxcTEAOZDk6elZro2ePXuiXr16f+a26BlhAICIiIiIqIZTqVRwd3dHdHQ0\nGjRoAACIjo6ucDJmbGwMZ2dnxMTEKJOy6OhoeHl5PdMx12arV69GTk4OPv30UxgYGFT3cPRIkoQW\nLVrg+vXryM3NhaWlpfKdEAJnzpyBiYkJmjRp8sRtNm/eHM2bN8fMmTOh0+mwYMECfPDBB9i2bRsm\nTZqkrCTw8PDA1KlTK/2e6NlhEkAiIiIiolpgzJgx+Oqrr6DT6ZCamor//Oc/GDt2LAAgJiYGn3/+\nuVJ37NixWLlyJYQQSE5OxrZt25S69GhFRUX44osv4OTkhAkTJlT3cCr0yiuvIDs7G2+99RbUajUA\nefK/ePFiXLhwAWPHjoW5uflj20lJScGFCxf0ylQqFTw8PJT/DQCjRo1C/fr18c9//hP/+9//yrVz\n48YN3Lt378/dFD0TXAFARERERFQLzJ8/HwsXLkTPnj1haGiITz75BEFBQQDkJev/+9//8NprrwEA\nFi5ciAULFiA0NBSGhoZYvnw5OnXqVJ3DrzU2b96MxMREzJ8//4km0dVh2rRpuHXrFr744gvs3bsX\n/v7+uHnzJq5fv44BAwZg2bJlT9TOvXv30KFDB3h7e6Np06awtrbG3bt3ERkZieHDh2PUqFEAAAsL\nC4SHh2P8+PHo3r072rZti/r166OwsBBRUVG4desWfvjhB9SvX78K75oqAwMARERERES1gLGxMRYs\nWFDhd61atcIPP/ygfDYxManwKDh6vA4dOiAiIkIvCV5VMTc3R0REBGxtbR9aZ/bs2ZgwYYLe5FqS\nJCxbtgwzZsxAREQEsrOz0aNHDwQGBiIgIEDveicnJ0RERMDb27tc2wEBAbh//z5Onz6N+Ph4FBYW\nIjQ0FIGBgWjdurVe3SZNmuDkyZM4ffo0zpw5g/z8fJiYmMDFxQWhoaFwdnb+cw+DngkGAIiIiIiI\niEr8fuJblQwMDNCzZ89H1vH19dXL5v+gxo0bo3Hjxo+83tTU9JF9eHl5PVV+iI4dO6Jjx45PXJ9q\nFgYAiIiIiGoQtVqNpKQkHDhwoMr6iImJQaNGjaqsfSIiqpkYACAiIiKqQYqKihAVFYW1a9dWWR/X\nrl1TknwREVHdwQAAERERUQ1iaWmJzp07Y+fOnVXWx7Rp02pscjOSFRYW4rfffsOGDRuqrI/r169z\nKTdRHcMAABERERFRDaNWqys8oq0ypaamQqfTVVn7RFTzMABARERERFTDWFlZISQkBF9++WWV9TF9\n+nSYmJhUWftEVPOoqnsARERERERERFT1uAKAiIiIiIioxK1bt/DLL78gKSkJlpaW8PHxQUhICAwM\nDKqsz5SUFPz0009ITExEcXEx7O3t0ahRI7Rr1w62trZKvS+//BKbNm3Cnj174O7u/th2x44di7y8\nPHz//fdVNnaqXRgAICIiIiKiOq+4uBijR49GWFgY3Nzc4OPjg4yMDERGRsLLywt79uyBn59fpfap\n0+kwZ84cfPHFFzAyMoKvry9MTEyQmJiIW7duwdjYGHl5eUr9uLg4nD9/HsXFxU/UfmxsLHJzcyt1\nzFS7MQBARERERER13rp167Bz5068/PLLWLNmjfLG//Dhw+jVqxemTJmC06dPV2qfGzZswKJFizBu\n3DisWbMGpqamyncpKSnYs2fPn2r/yJEjf3aI9BfDAAARERERUS2QkZGBv/3tb0hISEBRUREGDhyI\nd955B5IklaublpaGGTNmIDk5GUVFRRg6dCjefPPNahh17REVFQUAeOmll/SW+/fo0QP16tXD7du3\nK73PY8eOAQBeffVVvck/ADg5OeHll19+6LWHDh3Cli1bUFBQAA8PD4waNQrt27fXq/Pll1+iqKgI\nb731llL2r3/9C+np6XjttdewevVqnDlzBkII+Pr6YsaMGXB0dKzEO6SahkkAiYiIiIhqgVmzZsHR\n0RFHjhzBoUOH8O2332Lfvn0V1n3rrbfg6emJI0eOICIiAuvWrUN4ePgzHnHt0qtXLwAo99b93Llz\niIuLQ58+fSq9zwYNGgAAtm7disLCwie+bvbs2Zg2bRrMzMzg4uKCf//73wgMDMTPP/+sV2/Tpk1Y\nt26dXtm///1vLF26FF26dMFPP/2EVq1awdXVFUuWLEGbNm1w586dP39jVGMxAEBEREREVAv88MMP\nGDt2LADAzMwMQ4cOfWhyt127dil1LSwsMGTIEOzateuZjbU26tu3L7777jscPnwYzZs3x9ChQ9Gj\nRw/069cPM2fOxNq1ayu9z9dffx3t2rXDihUr4OzsjB49euCNN97Arl27kJmZ+dDr8vLycPXqVaxa\ntQorVqzAiRMnIEkSli9f/kT9pqenIygoCPv378e8efPwxRdf4Pjx40hKSsLUqVMr6/aoBmIAgIiI\niIiohtNoNEhNTYWrq6tS5urqivj4+HJ18/PzkZWVBRcXl8fWpTIajQYXL15EYmIinJycYG9vDycn\nJ2g0Gly5cgXJycmV3qetrS3Onj2LPXv2YMyYMUhNTcXKlSsxZMgQuLu7491334UQotx1s2bNgrGx\nsfK5YcOGaNasGa5fv/7Efc+dO1fvc+vWrTFgwAAcOXKkSu6VagbmACAiIiIiquEMDQ1hbW2N7Oxs\npSw7OxsODg7l6pqZmcHc3Bw5OTlKwOBhdanMvHnzsGjRIqxbtw6TJ09WyqOjo9GpUyf06tULV65c\ngZmZWaX2q1Kp0L9/f/Tv3x8AUFBQgGPHjuHNN9/EwoUL4ebmhhkzZuhdU69evXLtWFtb4/79+0/U\np62trV6AqFSzZs0ghMD9+/fh7Oz8B+6GajquACAiIiIiqgVCQkJw8OBBAIAQAgcPHkS3bt0AyJPG\ne/fuAQAkSUJwcPBD61LFvv/+e5iZmWHSpEl65V5eXhg4cCCioqJw4cKFKh+HmZkZ+vTpo2w5OHDg\nQKX3kZubC41GU648PT0dAGBlZVXpfVLNwBUARERERES1wOLFizFw4EDcuHED0dHRsLKywvjx4wEA\np06dwrBhw5CWlgYAWLZsGQYNGoQrV67g7t27cHZ2xksvvVSdw6/xLCwsUFhYiISEBHh4eOh9d/fu\nXQCVPzEuKCh46IqCrKwsAICJiUml9gnI2x327duHAQMGKGVFRUU4ePAg3Nzc0LRp00rvk2oGBgCI\niIiIiGoBHx8fREZG4vbt2zA3N4e3tzdUKnlBb1BQkF729ubNm+Py5cu4desWLC0t4e3tXeFxgVTm\nb3/7G6ZMmYLBgwfjww8/RNu2bZGUlIT169fj4MGDCAoKQqtWrSq1z7///e+4desWRo0ahRYtWsDd\n3R35+fk4evQoPvzwQxgYGJRb/l8ZTE1N8eqrr0Kr1aJLly5ITk7GP//5T9y9excbN25U/q7or4cB\nACIiIiKiWsLExAQtW7YsV25oaAhbW9tydX19fZ/V0Gq9yZMnw8zMDIsXL8YLL7ygLJF3cXHBzJkz\nsWDBgkoPorzwwgtYv3495syZg4yMDKXcxsYGwcHBePvttxEUFKSU29vbo2HDhjA0LD+Nc3d3L5cw\n0MPDA3l5eeXq2tvbY926dfjHP/6BmzdvKnU3btyorCqhvyYGAIiIiIiIiACMHj0ao0ePhlqtRnx8\nPOzs7GBtbV1l/Q0aNAiDBg0CAOTk5CAlJQX29vblgjml3nnnHbzzzjsVfrd9+/ZyZbt3735o3336\n9MGNGzeQnJwMjUYDd3f3P3AHVNswAEBERERERPQAIyMjeHt7P9M+raysqiX5HrP91y0MABARERHV\nIGlpafjhhx9gbm5eZX2o1WqMGzeuytonIqKaiQEAIiIiohrEwcEBgwYNws6dO6usj2nTplVpgIH+\nPCEECgsLkZqaWmV9FBYWVlnbVHP9+OOP0Ol01T0MqiYMABARERER1TCpqanYvn07Dh48WGV9ZGRk\nYOrUqVXWPtVM1bHNgGoOBgCIiIiIiGoYJycnTJgwAV9++WWV9TF9+nSuBCGqY3jAIxERERERESnS\n09OxY8cO5YhA+utgAICIiIiIiAjA9evXMWLECHh7e0OlUsHc3BxjxozBvXv3Kr2vkJAQNGrU6Il+\n/vWvf1V6/49y69YtjBgxAnv37n2m/VLV4xYAIiIiIiKq8y5evIiQkBBYWFhgwYIFaNWqFW7cuIH3\n338fnTp1wqlTp1C/fv1K62/atGnIyclRPmdkZGD27Nnw9fXF3//+d726HTp0qLR+qW5jAICIiIiI\niOq8d999Fzk5OYiIiEDHjh0BAJ06dUKHDh3g6+uLN998E2FhYZXW36hRo/Q+x8TEYPbs2fDy8tJL\nzpifn4+ioiIIISBJEmJjYxETE4OWLVvC0tISWVlZMDU1hZmZmV57xcXFyMvLg6WlJYyMjMr1n5mZ\niTt37sDAwABubm5wcXF5onHn5eWhuLgYZmZmMDU1/QN3TtWJWwCIiIiIiGqB3NxcjB8/HqGhoQgO\nDsaKFSseWjc7OxtjxoxR6q5ateoZjrR2On/+PGxtbZXJf6nmzZvD29sb//3vf5Gbm/vMx/XGG2/A\n3t4eBw4cgK+vLzw9PREYGIgTJ07g/v37sLe3x8KFC8tdt2PHDtjb25c7SeLy5cvo3bs3HB0d0b59\ne7Rt2xaurq4ICAh47Fg2bNgAZ2dnTJw4Efn5+ZV2j/TscAUAEREREVEtMHfuXJiamuLQoUPIy8tD\nu3bt4Ovri9DQ0HJ1Z82aBTs7O2zZsgU5OTlo06YNfH19ERwcXA0jrx0sLCyQlpYGtVqt98ZcCIHM\nzEyo1WpcuXIFnTp1qpbxvfLKK1i+fDm6du0KIQSMjY2RlZX1VG1cunQJQUFBsLOzw/fff49u3brB\nwsICcXFxiIiIeOh1ubm5mD59Onbs2IHPPvsMr776KiRJ+rO3RNWAKwCIiIiIiGqB7du34+WXXwYg\nT1ZffPFFbNu27bF1raysMGLECGzfvv2ZjbU26t+/P9RqNT766CO98hUrViAjIwOAnB2/usyfPx9D\nhw6Fi4sLXF1dYW9v/4faKCgowK5duzBgwABYW1vDwMAAXl5eyt/L70VGRqJ9+/Y4ffo0Tp48ib//\n/e+c/NdiDAAQEREREdVwGo0GycnJcHNzU8rc3NwQGxtbrm5BQQEyMjLg6ur62LpUZsGCBejevTs+\n+OADBAQEYNKkSejSpQvmzZuH9u3bA0C5ffbPUvfu3f90G0ePHkWjRo3g7+//RPV37dqFTp06oW3b\ntjh//jzatWv3p8dA1YsBACIiIiKiGs7Q0BCWlpbIzs5WyrKzsyt8C2xqagpTU1O9DPMPq0tlrKys\n8NNPP2Hv3r0YPnw4nJ2dMWzYMNy6dQu2trYAgGbNmlXb+Ozs7J6qvhCiXFlBQQGsra2fuA0TExOo\nVCrcvXtX7++Jai8GAIiIiIiIaoHAwEAcOXJE+XzkyBEEBgYCkFcIZGZmAgAkSULnzp316h4+fFip\nSw+nUqnw/PPP45133sGnn36K119/HYaGhjhx4gQCAwP1VmDUBDY2NgBQYS6A27dvlyvz8fHBjRs3\nnjiZ4XPPPYeff/4ZiYmJCAgIwOnTp//cgKnaMQBARERERFQLLF68GF999RVmzpyJESNGQAih7Ns+\nfvw4GjVqpNRdunQpli9fjpkzZ2Lo0KEwMzPDuHHjqmvotYJGo0FqaqpeWUpKCkaPHg2NRoMlS5ZU\n08gezt7eHq6urjhw4ADy8vKU8qioqApPfnj11VeRk5OD6dOno7CwUO+7h2X1b9u2Lc6ePYsmTZqg\nW7du2Lx5c+XeBD1TPAWAiIiIiKgW8PPzw8WLFxEZGQlra2v4+PhApZLf53Xq1Annz59X6rZt2xYX\nLlxAZGQkbG1t4ePjw8Rtj5GVlQVXV1e0atUKDRo0QFJSEiIjI2FhYYEffvgBnTt3ru4hVuijjz7C\nlClT4OPjgx49eiA7OxsnT55Ev379yk3Wp0yZgjt37mDx4sX4+eef0alTJ+UUgHPnziElJaXCPpyc\nnBAREYHXX38d48ePR2RkJBYvXgwDA4NncYtUiRgAICIiIiKqJUxNTcudUw/Iyenq169frqy6jqyr\njWxsbPDDDz/g3LlzSExMRP369fHKK69g4MCBylL7qmRnZ4c1a9bA09NTr3z06NFo164dzM3NK7xu\n0qRJaN26NcLDwxEdHY3WrVtj5cqVKCwsRJcuXeDn56dX/9NPP8XLL7+M77//HlFRUTAyMkKXLl3w\n3nvvKXUaNGiANWvW6AU9jIyMsHLlSvTr1w9xcXG4fv06WrZsWYlPgJ4FBgCIiIiIiKjOMzQ0xAsv\nvIAXXnihWvq3tLTE1KlTy5UHBQUhKCjokdf6+/tXmNm/cePGFdZv0qQJZs2a9dD2nJ2dKxwLADz/\n/POPHAvVbMwBQERERERERFQHcAUAERERUQ3z22+/4f3336+y9s+dO4fg4OAqa5+IiGomBgCIiIiI\napDQ0FAYGRlVaR8vvvgiAgICqrQPIiKqeRgAICIiIqpBOnbsWGGSN6p7jh8/jpkzZ1ZZ+ydOnMDA\ngQOrrH0iqnkkIYSo7kEQEREREVGZyMhIXLlypcr7adWqVbks8UT018UAABEREREREVEdwFMAiIiI\niIiIiOoABgCIiIiIiIiI6gAGAIiIiIiIiIjqAAYAiIiIiIiIiOoABgCIiIiIiIiI6gAGAIiIiIiI\niIjqAAYAiIiIiB4QHR2N2bNn48GTknU6HaKionD48GHcv3+/wuuKiooQHh6OHTt24NKlS+W+z8/P\nx/Hjx7Fjxw4cPXoUeXl5jxzHpUuX8NNPP6G4uPiR9fLz87Fhwwa8+eabWLhw4RPcYe1SWFiImTNn\nIisrq7qHQkRU6zEAQERERPSAyZMnw93dHZIkAQDCw8NhZWWF9u3bo3fv3ti5c2e5a+Li4uDv74+5\nc+di79696NevH6ZNm6YEEa5duwYnJyfMmTMHO3bswPz58+Hp6YnvvvuuwjGcPHkSXbt2Ra9evR47\n8Z01axY2btyIoKAg9OrV60/evezUqVOwt7eHVqutlPb+DFNTUxgaGuLtt9+utjFs3boVN27cKFee\nmJiImJiYh16XmZmJ8+fP4+bNm0/UT3FxMfbu3YsVK1Zg7969f3i8NVVcXBzWrl1b3cMgqtMYACAi\nIiIqER4ejkuXLmHq1KlKWYcOHXD79m2kp6fDxcWlwuv+8Y9/wNbWFr/88gs2bdqEn3/+GRs2bFCC\nBW5ubrh58yaOHz+O7777DkeOHMH06dMxdepU6HQ6vbYSExMxduxYzJs377HjjYqKwrFjxxAUFAQ/\nPz/4+Pgo3xUUFODq1au4fv16hasI4uLicP78eVy+fBmZmZlKuVqtRnR0NDIyMhAVFYWoqCikpaUB\nAO7du1du5UJMTAxycnIAAFqtFlFRUVCr1UhLS8OpU6f02o6Pj8eFCxeQnJxcbjyFhYU4f/48zp8/\njxs3buitwHjrrbewZcsWXL9+/bHPpLIdPnwY8+fPh7e3t1I2fPhwuLq6ws3NDX369Knwuq+++gr1\n69fHzJkz0bNnT4SEhCA1NfWRfY0cORLLly+HJEmwsLColPHv3LkTw4cPr5S2/iw3NzesW7cO27Zt\nq+6hENVdgoiIiIiEEEIMGTJEvPLKKw/93t3dXSxZskSvTKfTCXNzc/H111/rlffu3VuMHz/+oW2t\nXLlSWFlZCbVarZSp1WoRHBwsvvrqKxEeHi4AiOTk5Ie2MWLECGFrayvatGkjhg8fLsLCwoQQQixd\nulS4uLiI559/XvTt21d4e3uLffv2Kde9/fbbok2bNmLw4MFi4MCBwsHBQaxfv14IIUR8fLzo3r27\nACCGDRsmhg8fLr755hshhBD29vZi165demNo2rSpWLdunRBCiMTERAFATJw4UbRs2VL0799fRERE\niDt37oigoCDh6+srhg4dKpo0aSJGjBghCgoKhBBCnDlzRri7u4s+ffqI4cOHi379+olXX31Vr5++\nffuKN99886HPoirodDrRpk0bsXbtWr3yiIgIERUVJebNmyeaN29e7rqTJ08KSZJERESEEEKIgoIC\n0bFjR/Hiiy8+sj8LCwtx4MCBCr/LyckRxcXFFX5XUFAg0tPTRX5+frnvVq1aJVq0aPHIfh+nuLhY\nJCUlCa1Wq5RpNBqRnZ390Gvy8vJEenq6KCoq0ivfvXu38PLyKldORM8GAwBEREREJRwcHJTJbkUq\nCgAkJycLACI8PFyvfOrUqaJ79+4VtnP79m3h6uoqPvnkE73y119/XYwcOVIIIZ4oACCEEG3bthXL\nly9XPv/444/C3t5e3L9/XykLDw8XNjY2IjMzUwghT84edOzYMWFmZiZyc3OFEEIcP35cABAajUav\n3pMGAKZPny50Op1Sp2PHjuKNN95QPms0GhEcHCzee+89IYQQkydPFi+//PIj73P+/PnC39//kXUq\n29GjR4WxsbHIycmp8Pv33nuvwgDAG2+8Idq0aaNXtnnzZmFkZKQX8Cl1584d4e/vLyRJEk2aNBH+\n/v7i6NGjQqfTiWXLlglPT0/RqlUr0aBBA9GvXz8RHR2tXDtp0iTh6ekp2rVrJxo3bixat24tIiMj\nhRBCHD58WHh5eQlTU1Ph7+8v/P39xa5du0RcXJwAIG7fvq20U1RUJACIU6dOCSHkIIeRkZFYsGCB\n8PLyEs2bNxc3b94UN2/eWZgZBwAAChZJREFUFL179xZeXl6idevWwsvLS/zrX/9S2jly5Iho0aKF\naNmypfD39xdNmzZVgktCCKHVaoWjo6P47rvvnuRXQESVzLDalh4QERER1SAajQZpaWlwdHR8qutE\nyVL10pwBpSRJKre8HwAiIyPx/PPPY+TIkZg1a5ZSvn37duzbtw9nz579A6Mv89///hd2dnZYtWqV\n3hizs7MRGRmJ4OBgpKWl4cMPP8TVq1eRnJwMtVqNgoIC3Lx5E23btv1T/QPAhAkTlOeRlJSE06dP\nw8fHB7Nnz1bq6HQ6HD9+HADQt29fTJgwAYmJiejfvz+6d++Opk2b6rXp6OiIpKSkPz22pxEREYE2\nbdrA0tLyqa67f/8+GjdurFfWuHFjqNVqxMXF6W0nAICGDRvi3LlzMDY2xqpVq9CzZ08A8jaCzz//\nHD///DO8vLyg0+nw2muvYeLEifjpp58AAPPmzcP69euVtt577z1MnToVp06dQvfu3TF79mysXLkS\n586dU+rEx8c/0X2o1Wrk5+fj7t27UKlUKCgoQNu2bTFq1Cjs378fKpUKN27cQNeuXdGsWTOEhIRg\n3rx5GDdunN7f9oPbRlQqFQIDAxEREVFjtiYQ1SUMABAREREBMDQ0hLW1NbKzs5/qOicnJ5iZmZU7\nHeDevXuoX7++XtmBAwcwatQozJ07F2+99Zbed4sXL4YkSRgyZAgAID09HQAwbNgwTJgwARMnTnyi\n8RQVFcHd3V2ZRJbq1asXWrRoAZ1Oh+DgYIwaNQpfffUVbG1todVqYWdnh4KCgke2rVKp9PbmA6gw\nv4CNjY3eeACga9euaNCggVLes2dPWFtbAwCGDh2Krl274sCBAzh48CDmzp2LoUOHYs2aNUr9rKws\n2NvbP9EzqCxxcXFwdXV96usKCgpga2urV2ZiYqJ896TCwsLg4+ODAwcOKGW2trY4cuQI8vLyYGFh\nATMzMyxbtgx3795FcnIy0tLScOHCBajVahgZGT312H9v9uzZUKnktGFnz57FjRs3YGtri6+//lqp\n4+npiX379iEkJAStW7fG6tWrkZ2djeeffx4BAQHl8hm4ubkhOjr6T4+NiJ4eAwBEREREJQIDA3Hp\n0iW89NJLT3yNJEno168ftm7digkTJsDAwAAxMTH43//+h2+//Vapt3r1asyZMwebN29G//79y7Wz\nZcsW5OfnK59Pnz6NCxcu4N1330WLFi2eeDwhISHYvXs3WrRoAXd3d6Vcq9XCwMAASUlJuHfvHsaO\nHQtPT08AKJeZvXRinpubqzeZ9/T0xNWrVzF48GAA8ukGj5vIeXl5oWHDhrh9+zamTJmi913pKQNa\nrRYuLi4YP348xo8fjz179mDEiBFYvXq1Mvm8dOkSunTp8sTPoTJYWVk9Msv/w3h5eeHatWt6ZXFx\ncZAkCV5eXk/cTnp6erkgUr169bB69WoIIZCWloZ27dph4sSJeOmll2BlZYUbN27g0KFDKCwsfKoA\nQEUnPhgZGen9/jMyMmBoaKgEM0pNmzZNSUC5cuVKDBkyBPv27cPUqVMRHx+P1atX48UXX1Tq5+Xl\nwcrK6onHRkSVhwEAIiIiohLjxo3De++9h08//VSZeCYkJCgT9pSUFHz++ef4z3/+g9DQUCxatAgA\nsGLFCnTr1g1du3ZFu3btsGvXLrz44osYNmwYAPlYvxkzZsDV1RUffPABPvjgA6XPPXv2wN3dHc2b\nN9cbS+kKgNatW8PJyemJ72HMmDG4fPky2rdvj/79+8POzg4JCQk4dOgQYmNj4eLigv79+2Pw4MEY\nOHAg4uLiyh012Lx5c3To0AE9evRAo0aN8Nxzz2HChAmYNWsWJk+ejOjoaBgbG+P69etP9IZ8+/bt\nGD9+PM6fP482bdpArVbj8uXL6Nmzp/K2HwAaNWoEIQS+//57zJgxQ/kd5ObmIjw8HPv373/i51AZ\n2rVrV+Gxj48THByMDRs2IDExUXk+u3btQocOHWBubv7E7XTq1AlXrlzB5MmTlWfxoFOnTiEjIwML\nFy5UtlyEhYXp1TE1NVVWYZRydHRUAlWNGjUCIP+NPk779u0BAPXr10ffvn0rrCNJEkJDQxEaGoql\nS5fi/fffx6JFi/QCAFevXsXIkSMf2x8RVT5J/H4dFxEREVEdpdVq4efnhw8//FBZil9cXIxff/21\nXF07Ozs0bNhQ+VxYWIhjx44hKysLTZo0QZs2bZTvcnJyHnoWvK+vb7k3qgCQnZ2NW7duoXXr1jA0\nfPg7m2vXrsHBwQHOzs565XFxcbhy5QpycnLg6uqKtm3bKkuxhRA4ceIEEhIS4OnpiQ4dOuDixYvw\n8fFR9rsLIXDr1i3k5OTA2dlZWS1w/fp1XL16FTY2NggJCcHNmzfh4uICR0dHZWLfsmVLmJqalnu2\nZ8+eRXx8PExMTNC0aVM0adIEgPxG+PTp00hLS4OJiQlatmypTEwBYPny5Th48KDeUvhnITU1Fd7e\n3jh69Kgy+QWAhQsX4vLly7h69SpiY2OVowC/+eYbWFhYQKfToX///rhz5w4mT56MK1euICwsDEeO\nHNFr5/eMjY2xb98+ZftGQkICBgwYAAsLCwwaNAgmJiaIjo7GzZs3ERYWhvT0dLRs2RLdu3dHt27d\ncPnyZZw+fRrnzp1DdnY2rKyscOvWLbRp0wajRo2Co6Mjhg4dioCAAIwfPx6nTp3CjBkzkJOTg+PH\njyM8PBynTp1Cx44d8dNPP+G5554rt8Vj5cqV+OijjzB69Gg0adIEeXl5OHHiBCZMmID+/fujd+/e\n6NChA+rVq4e8vDysWrUKEydOVI61jI6ORuPGjfHbb7+Vy5NARFWPAQAiIiKiB5w5cwbr16/X239O\n1UetVmPMmDFYtGhRueXwz8Ls2bMRExODrVu3KmXHjh2rMCHhoEGDlGX3Op0Oe/fuxbVr12BlZYWB\nAwfCw8PjkX2FhYWha9eucHFxUcqEEIiIiMC1a9eg0Wjg4eGBrl27ol69egDkVSlhYWHIyspCy5Yt\nERgYiEOHDmHw4MFK4Cg5ORlnzpxBQUEB2rdvjwYNGkCn02Hnzp24e/cuPDw8MHToUOzduxehoaGw\nt7dHUlISfv75Z2V1xoNiY2Nx+PBhJCQkwMrKCn5+fggICICJiQkuXbqEEydOIDc3F+bm5ujYsSMC\nAgKUFQpvvvkm0tPT8c033zzlb4KIKgMDAERERERED5Gfn4/evXtj/fr1yj53+mOSkpLQv39/7Nu3\n76lP2yCiysEAABEREREREVEdUD6bCBERERERERH95TAAQERERERERFQHMABAREREREREVAcwAEBE\nRERERERUBzAAQERERERERFQHMABAREREREREVAcwAEBERERERERUBzAAQERERERERFQHMABARERE\nREREVAcwAEBERERERERUBzAAQERERERERFQHMABAREREREREVAf8H2Lbrbu7onk4AAAAAElFTkSu\nQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image, display\n",
    "Image('images/08_transfer_learning_flowchart.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import time\n",
    "from datetime import timedelta\n",
    "import os\n",
    "\n",
    "# Functions and classes for loading and using the Inception model.\n",
    "import inception\n",
    "\n",
    "# We use Pretty Tensor to define the new classifier.\n",
    "import prettytensor as pt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用Python3.5.2（Anaconda）开发，TensorFlow版本是："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.6.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "PrettyTensor 版本:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.7.4'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pt.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 载入CIFAR-10数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cifar10"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "cirfa10模块中已经定义好了数据维度，因此我们需要时只要导入就行。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cifar10 import num_classes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "设置电脑上保存数据集的路径。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# cifar10.data_path = \"data/CIFAR-10/\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CIFAR-10数据集大概有163MB，如果给定路径没有找到文件的话，将会自动下载。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data has apparently already been downloaded and unpacked.\n"
     ]
    }
   ],
   "source": [
    "cifar10.maybe_download_and_extract()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "载入类别名称。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data: data/CIFAR-10/cifar-10-batches-py/batches.meta\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['airplane',\n",
       " 'automobile',\n",
       " 'bird',\n",
       " 'cat',\n",
       " 'deer',\n",
       " 'dog',\n",
       " 'frog',\n",
       " 'horse',\n",
       " 'ship',\n",
       " 'truck']"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "class_names = cifar10.load_class_names()\n",
    "class_names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "载入训练集。这个函数返回图像、整形分类号码、以及用One-Hot编码的分类号数组，称为标签。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data: data/CIFAR-10/cifar-10-batches-py/data_batch_1\n",
      "Loading data: data/CIFAR-10/cifar-10-batches-py/data_batch_2\n",
      "Loading data: data/CIFAR-10/cifar-10-batches-py/data_batch_3\n",
      "Loading data: data/CIFAR-10/cifar-10-batches-py/data_batch_4\n",
      "Loading data: data/CIFAR-10/cifar-10-batches-py/data_batch_5\n"
     ]
    }
   ],
   "source": [
    "images_train, cls_train, labels_train = cifar10.load_training_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "载入测试集。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data: data/CIFAR-10/cifar-10-batches-py/test_batch\n"
     ]
    }
   ],
   "source": [
    "images_test, cls_test, labels_test = cifar10.load_test_data()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在已经载入了CIFAR-10数据集，它包含60,000张图像以及相关的标签（图像的分类）。数据集被分为两个独立的子集，即训练集和测试集。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Size of:\n",
      "- Training-set:\t\t50000\n",
      "- Test-set:\t\t10000\n"
     ]
    }
   ],
   "source": [
    "print(\"Size of:\")\n",
    "print(\"- Training-set:\\t\\t{}\".format(len(images_train)))\n",
    "print(\"- Test-set:\\t\\t{}\".format(len(images_test)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 用来绘制图片的帮助函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这个函数用来在3x3的栅格中画9张图像，然后在每张图像下面写出真实类别和预测类别。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_images(images, cls_true, cls_pred=None, smooth=True):\n",
    "\n",
    "    assert len(images) == len(cls_true)\n",
    "\n",
    "    # Create figure with sub-plots.\n",
    "    fig, axes = plt.subplots(3, 3)\n",
    "\n",
    "    # Adjust vertical spacing.\n",
    "    if cls_pred is None:\n",
    "        hspace = 0.3\n",
    "    else:\n",
    "        hspace = 0.6\n",
    "    fig.subplots_adjust(hspace=hspace, wspace=0.3)\n",
    "\n",
    "    # Interpolation type.\n",
    "    if smooth:\n",
    "        interpolation = 'spline16'\n",
    "    else:\n",
    "        interpolation = 'nearest'\n",
    "\n",
    "    for i, ax in enumerate(axes.flat):\n",
    "        # There may be less than 9 images, ensure it doesn't crash.\n",
    "        if i < len(images):\n",
    "            # Plot image.\n",
    "            ax.imshow(images[i],\n",
    "                      interpolation=interpolation)\n",
    "\n",
    "            # Name of the true class.\n",
    "            cls_true_name = class_names[cls_true[i]]\n",
    "\n",
    "            # Show true and predicted classes.\n",
    "            if cls_pred is None:\n",
    "                xlabel = \"True: {0}\".format(cls_true_name)\n",
    "            else:\n",
    "                # Name of the predicted class.\n",
    "                cls_pred_name = class_names[cls_pred[i]]\n",
    "\n",
    "                xlabel = \"True: {0}\\nPred: {1}\".format(cls_true_name, cls_pred_name)\n",
    "\n",
    "            # Show the classes as the label on the x-axis.\n",
    "            ax.set_xlabel(xlabel)\n",
    "        \n",
    "        # Remove ticks from the plot.\n",
    "        ax.set_xticks([])\n",
    "        ax.set_yticks([])\n",
    "    \n",
    "    # Ensure the plot is shown correctly with multiple plots\n",
    "    # in a single Notebook cell.\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 绘制几张图像看看数据是否正确"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vT7AVrk9FhOpRXDanU85yyHJzy9RlbzI9djQaoadNEffEAw0Y8dff8KUvf/lY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\nw8PDY0j8f/sJk3mN/fWjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1af78ecac18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Get the first images from the test-set.\n",
    "images = images_test[0:9]\n",
    "\n",
    "# Get the true classes for those images.\n",
    "cls_true = cls_test[0:9]\n",
    "\n",
    "# Plot the images and labels using our helper-function above.\n",
    "plot_images(images=images, cls_true=cls_true, smooth=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 下载Inception模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从网上下载Inception模型。这是你保存数据文件的默认文件夹。如果文件夹不存在就自动创建。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# inception.data_dir = 'inception/'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "如果文件夹中不存在Inception模型，就自动下载。\n",
    "它有85MB。\n",
    "\n",
    "更多详情见教程#07。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading Inception v3 Model ...\n",
      "Data has apparently already been downloaded and unpacked.\n"
     ]
    }
   ],
   "source": [
    "inception.maybe_download()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 载入Inception模型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "载入模型，为图像分类做准备。\n",
    "\n",
    "注意warning信息，以后可能会导致程序运行失败。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "model = inception.Inception()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 计算 Transfer-Values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "导入用来从Inception模型中获取transfer-values的帮助函数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from inception import transfer_values_cache"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "设置训练集和测试集缓存文件的目录。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path_cache_train = os.path.join(cifar10.data_path, 'inception_cifar10_train.pkl')\n",
    "file_path_cache_test = os.path.join(cifar10.data_path, 'inception_cifar10_test.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Inception transfer-values for training-images ...\n",
      "- Processing image:  36520 / 50000"
     ]
    }
   ],
   "source": [
    "print(\"Processing Inception transfer-values for training-images ...\")\n",
    "\n",
    "# Scale images because Inception needs pixels to be between 0 and 255,\n",
    "# while the CIFAR-10 functions return pixels between 0.0 and 1.0\n",
    "images_scaled = images_train * 255.0\n",
    "\n",
    "# If transfer-values have already been calculated then reload them,\n",
    "# otherwise calculate them and save them to a cache-file.\n",
    "transfer_values_train = transfer_values_cache(cache_path=file_path_cache_train,\n",
    "                                              images=images_scaled,\n",
    "                                              model=model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing Inception transfer-values for test-images ...\n",
      "- Data loaded from cache-file: data/CIFAR-10/inception_cifar10_test.pkl\n"
     ]
    }
   ],
   "source": [
    "print(\"Processing Inception transfer-values for test-images ...\")\n",
    "\n",
    "# Scale images because Inception needs pixels to be between 0 and 255,\n",
    "# while the CIFAR-10 functions return pixels between 0.0 and 1.0\n",
    "images_scaled = images_test * 255.0\n",
    "\n",
    "# If transfer-values have already been calculated then reload them,\n",
    "# otherwise calculate them and save them to a cache-file.\n",
    "transfer_values_test = transfer_values_cache(cache_path=file_path_cache_test,\n",
    "                                             images=images_scaled,\n",
    "                                             model=model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "检查transfer-values的数组大小。在训练集中有50,000张图像，每张图像有2048个transfer-values。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50000, 2048)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transfer_values_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相同的，在测试集中有10,000张图像，每张图像有2048个transfer-values。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(10000, 2048)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transfer_values_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 绘制transfer-values的帮助函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_transfer_values(i):\n",
    "    print(\"Input image:\")\n",
    "    \n",
    "    # Plot the i'th image from the test-set.\n",
    "    plt.imshow(images_test[i], interpolation='nearest')\n",
    "    plt.show()\n",
    "\n",
    "    print(\"Transfer-values for the image using Inception model:\")\n",
    "    \n",
    "    # Transform the transfer-values into an image.\n",
    "    img = transfer_values_test[i]\n",
    "    img = img.reshape((32, 64))\n",
    "\n",
    "    # Plot the image for the transfer-values.\n",
    "    plt.imshow(img, interpolation='nearest', cmap='Reds')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input image:\n"
     ]
    },
    {
     "data": {
      "image/png": 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V6pwlc6XREVfcyGh8bkV3qyRnuxZHS6VK2Vemlx/qd8Ud6jroi2uPtxoqDMVb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\nIgkpCYuIJPT/AXzCtKiP5tRpAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe17f978940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transfer-values for the image using Inception model:\n"
     ]
    },
    {
     "data": {
      "image/png": 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9Tjg9blgRl4WlxzxAjyOQ9EOQUtMAaOqdL4ofb9stLsnrpHwrAKBjnF5M04DZ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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe17f92f9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_transfer_values(i=16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input image:\n"
     ]
    },
    {
     "data": {
      "image/png": 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79XFjuSNFRGTKKQmLiCSkJCwikpCSsIhIQkrCIiIJKQmLiCSkJCwikpCSsIhI\nQkrCIiIJTapizsz+APgV4BJgGHgG+FQI4ZUxMT8Abh7zbQH4mxBCzf4/dY311Odq9/XJF+JtR/Ku\n1iRww003ueKuucHX9mewNBAPMmcbluD72WiVeFVOKA+5xipXfBVRC+Z0ueLu/Xf3RGN2797tGmv7\nttdccYcOx6uw2ucuco1Vyg+74mbPmeWKGwjx/dA96Kyy6vbFNUTahR031BA/3obyvmrPgfyIL24g\n/jndf3Sva6w9+w654pauXOWKq694Pn+1q1WzFWePMiZ/JnwT8AXgeuBdQD3wHTMb24AqAH8LLAC6\ngIXA709yPSIiF4RJnQmHEO4c+7WZfQg4BFwNPD3mpaEQgq87o4jIBexMrwl3UD3znfgUk/vN7LCZ\nvWRmfzrhTFlEREad9lPUzMyAzwNPhxA2j3npK8BOYB9wJfBZYC3wa2cwTxGR89KZPMryIeAy4O1j\nF4YQ/m7Ml5vM7ADwXTNbGULYcarBnn91N/V12XHLls2fw7Iu3yMFRURSePzxJ3h8w5Pjlg0MxB9d\netxpJWEz+yvgTuCmEML+SPjPAANWA6dMwm9es5TZs5pPZzoiIsncccdt3HHHbeOWbdmylXs/8Juu\n7590Eh5NwO8D3hFC8Dwh+yqq141jyVpE5IIz2fuEHwLuA+4GBs1swehLvSGEvJmtAj4APAZ0A+uA\nB4EfhhA2Tt20RUTOD5M9E/4o1bPaH0xY/mHgYaBA9f7hTwAtwG7gH4E/OaNZioicpyZ7n3DNW9pC\nCHuAW05nIgEIVjvmmKNP10WXXuxa332/cb8rrqOjwxVXKcYrgKo3lMSF4Kus81TM4RwLZ1jR8T4B\nMpn43Y/Lnf3vVq3yVTq9tm17NObJ737PNdYlb7rUFXf5xe93xR3eG79yt3njS66xduz19VHsOXzQ\nFZdtjld3Zet9d7MWRhwN6wDK8QMul/P1gWxu8d0BG5xVoZ64TCb2WXZ+oNCzI0REklISFhFJSElY\nRCQhJWERkYSUhEVEElISFhFJSElYRCQhJWERkYTO5ClqU2ooP0xdZDaZXO2WIgC/dPt7XOtbuMjX\n5qYwhcUJKXhvGXcXiDgLTiqOQpJy2XfzvHfbrlgRL/64717fE1UbG3ztaZqb4sckwNKli+MxK1e6\nxvr6Nx5xxe3d+ko8CBg6WorGNLf4Hq5VdrY3KjlalbW2trrGmjOn3RUX8B1vED92LVKsYRkVa4iI\nnBOUhEWCwI+eAAAK50lEQVREElISFhFJSElYRCQhJWERkYSUhEVEElISFhFJSElYRCQhJWERkYRm\nTMVcvpCnLl+7yuSGW98dHefKa692ra9YilcJAYSyo4UQEBy1ad6qtKmsvpvqSripHC+bzU7pOkvF\neGudWbN8rXAyzu1Rch4fI8X48ZZr87XSWrosXn0HsHHrJldc3tE2rPdYj2usjK/AlNJwfF9d8SZf\n+6uO2c6KueCrmDOL79NiZH+WSs42T+hMWEQkKSVhEZGElIRFRBJSEhYRSUhJWEQkISVhEZGElIRF\nRBJSEhYRSUhJWEQkoRlTMbd85Wo6I72i7nrf+6LjNDb7KqIqJV+lk69uCiqOqq6Ss0rPW73mqTjz\n9HoDf1Wat8rNE+d9n95edJ6OepWybx/grFoMzvOY4DmSzDfWm9a9yRVXKvuqtv71xZeiMQcOHHGN\nNb9jnituxdJl0Zhb3nWLa6xZs1pccfmRYVdcueI5RmKfK9/nDnQmLCKSlJKwiEhCSsIiIgkpCYuI\nJKQkLCKSkJKwiEhCSsIiIgkpCYuIJKQkLCKS0KQq5szso8DvACtGF20CPhNC2DD6eiPwIPDrQCPw\nBPCxEMKh2NhvvelWVq1cUTNm3ux4b63CgK9KKJvxVX55q7o8cd6xvD3mPONN5ViTGc9Tgeet0nP3\n5rP4Ps04C5mc7cjIZH3bI+uomCs7qxvnzetyxb3rPbe74t589XXRmJGREddYHe2+Pnm5xlw0Jput\nd41VKPjmVnZWrHqqX7OR/W6TOL+d7JnwbuBTwNWj/74HPGJml46+/nngLuAe4GZgEfDNSa5DROSC\nMakz4RDCP01Y9Idm9jvAW81sL/AR4N4Qwg8BzOzDwBYzuy6E8OyUzFhE5Dxy2teEzSxjZvcCzcBP\nqJ4Z1wFPHY8JIbwM7AJuOMN5ioiclyb9FDUzu4Jq0s0B/cCvhBC2mtlVQCGE0DfhWw4CvotYIiIX\nmNN5lOVWYB3QQfXa78NmdnONeMPxjMEv/++v0dzcPG7Z2992PTe+7a2nMUURkbPj8Q1PseGJ741b\nNtA/4P7+SSfhEEIJ2D765c/N7DrgE8DXgQYza5twNjyf6tlwTb/57++L3h0hIjLT3HH7rdxx+63j\nlm3Z8gof+I3fdn3/VNwnnKF6O9pzQAl4YzZmthZYRvXyhYiITDDZ+4T/BHic6q1qs4D7gXcA7wkh\n9JnZF4EHzewo1evFfwn8WHdGiIic3GQvRywAHgYWAr3Ai1QT8PELIp8EysA3qJ4dbwA+7hl46bKV\nrF5zcc2YsqMl0VQXYXh5ixg8vC2EPOt0Fzo45+9tl+RpSRS74f24ujrnYep4r5ng3O/ew8O3eV3H\nW33W9z4r3mM34xtv0cKF8XU697t3g/gOS2crrYo3jfmKPzwtqzKZ2vvAfcwy+fuE/0Pk9RHg90b/\niYhIhJ4dISKSkJKwiEhCMzYJb3jiO6mncEbW/9Pjqadwxh5dP7FK/dzy7fWPpZ7CGXvkHN8Hj64/\n9z8Hjz3+3WkdfwYn4SdTT+GMrH/s3D/41p/jSezb58UPwnN7H6xfvyH1FM7Y4xsu0CQsInIhUBIW\nEUlISVhEJKHTeYDPVMsB7Hj99XELBwYG2LL15XHLPDdAR+6hfsOUF2tMKLDo7x9g0+Yt45Z5b3jP\nertheOKcxRonG6uvv5+NmzaPH85brOGIy7p3lvNcYcJ77T/J/LPeYo0p5jreThLT19/PSxP3gTnb\nfkzhW/V0m6gaH1c9hracGOUazrffS8WiK65c8cUFxm/fgf4BNm8Zn4sykf25fcfO4/+NthAxb0XV\ndDGzDwBfSToJEZHpcX8I4au1AmZCEp4L3Aa8DuSTTkZEZGrkqPbifCKE0F0rMHkSFhG5kOkPcyIi\nCSkJi4gkpCQsIpKQkrCISEJKwiIiCc3IJGxmHzezHWY2bGY/NbNrU8/Jw8weMLPKhH+b49+Zjpnd\nZGaPmtne0fnefZKYz5jZPjMbMrMnzWx1irmeTGz+Zvalk+yTGfNUHDP7AzN71sz6zOygmX1rtDfj\n2JhGM/trMztiZv1m9g0zm59qzmM55/+DCdu/bGYPpZrzRGb2UTN7wcx6R/89Y2a3j3l9Wrf/jEvC\nZvbrwOeAB4CrgBeAJ8ysM+nE/DZSbQPVNfrvxrTTiWoBnqfahuqE+xXN7FPA7wK/DVwHDFLdHw1n\nc5I11Jz/qMcZv0/uOztTc7kJ+AJwPfAuqj14vmNmTWNiPg/cBdwD3AwsAr55lud5Kp75B+Bv+cU+\nWAj8/lmeZy27gU8BV4/++x7wiJldOvr69G7/EMKM+gf8FPgfY742YA/w+6nn5pj7A8DPU8/jDOZf\nAe6esGwf8MkxX7cBw8D7U8/XOf8vAf839dwm8R46R9/HjWO29wjwK2NiLh6NuS71fGPzH132feDB\n1HOb5PvoBj58Nrb/jDoTNrN6qj+Jnjq+LFTf9XeBG1LNa5LWjP5qvM3M/sHMlqae0Okys5VUz1zG\n7o8+4GecO/sD4JbRX5W3mtlDZjYn9YRq6KB65tgz+vXVVJ/xMnYfvAzsYmbug4nzP+5+MztsZi+Z\n2Z9OOFOeMcwsY2b3As3ATzgL238mPMBnrE6qLVYPTlh+kOpPn5nup8CHgJep/sr1aeCfzeyKEMJg\nwnmdri6qH6iT7Y+usz+d0/I41V8ddwAXAX8GPGZmN4z+gJ8xrPqUn88DT4cQjv8toQsojP7wG2vG\n7YNTzB+qz4bZSfW3qiuBzwJrgV8765M8BTO7gmrSzQH9VM98t5rZVUzz9p9pSfhUDHdz8XRCCE+M\n+XKjmT1L9eB7P9Vfi88X58T+AAghfH3Ml5vM7CVgG3AL1V+TZ5KHgMvw/R1hJu6D4/N/+9iFIYS/\nG/PlJjM7AHzXzFaGEHaczQnWsBVYR/VM/h7gYTO7uUb8lG3/GXU5AjgClKlewB9rPieejc14IYRe\n4BVgxtxNMEkHqB5s58X+ABj90B9hhu0TM/sr4E7glhDCvjEvHQAazKxtwrfMqH0wYf77I+E/o3pc\nzZh9EEIohRC2hxB+HkL4L1RvCPgEZ2H7z6gkHEIoAs8Btx5fNvorzq3AM6nmdbrMrJXqr8Cxg3JG\nGk1YBxi/P9qo/iX8nNsfAGa2BJjLDNonownsfcA7Qwi7Jrz8HFBi/D5YCyyj+utzcpH5n8xVVM8i\nZ8w+OIkM0MhZ2P4z8XLEg8CXzew54Fngk1Qvkv99ykl5mNlfAN+megliMfDfqO7Ar6WcVy1m1kL1\njOT4U6pXmdk6oCeEsJvqNb4/NLPXqD5u9I+p3q3ySILpnqDW/Ef/PUD1mvCB0bg/p/rbyRMnjnb2\njd4vex9wNzBoZsd/6+gNIeRDCH1m9kXgQTM7SvV65V8CPw4hPJtm1r8Qm7+ZrQI+ADxG9Y6DdVQ/\n4z8MIWxMMeeJzOxPqP7tYDcwC7gfeAfwnrOy/VPfCnKK20M+RvUDP0z1p801qefknPfXqCaoYap/\nPf0qsDL1vCJzfgfV223KE/79rzExn6b6R5Uhqslrdep5e+ZP9Y8sG6gm4DywHfifwLzU8x4z/5PN\nvQx8cExMI9V7cY+MJoF/BOannrtn/sAS4AfA4dHj52WqfxxtTT33Me/h70aPjeHRY+U7wC+dre2v\n5wmLiCQ0o64Ji4hcaJSERUQSUhIWEUlISVhEJCElYRGRhJSERUQSUhIWEUlISVhEJCElYRGRhJSE\nRUQSUhIWEUno/wMVBitmkXySDQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe17fdc1320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Transfer-values for the image using Inception model:\n"
     ]
    },
    {
     "data": {
      "image/png": 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0PbdQu2fztIz8tz8K25cu+J7fd7V0F0eqmgoYpCF18VOb8uceC7td/bOfurHO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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe17fd6b2b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_transfer_values(i=17)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## transfer-values的PCA分析结果"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "用scikit-learn里的主成分分析(PCA),将transfer-values的数组维度从2048维降到2维，方便绘制。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.decomposition import PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建一个新的PCA-object，将目标数组维度设为2。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "pca = PCA(n_components=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算PCA需要一段时间，因此将样本数限制在3000。如果你愿意，可以使用整个训练集。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "transfer_values = transfer_values_train[0:3000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "获取你选取的样本的类别号。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cls = cls_train[0:3000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "保数组有3000份样本,每个样本有2048个transfer-values。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3000, 2048)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transfer_values.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "用PCA将transfer-value从2048维降低到2维。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "transfer_values_reduced = pca.fit_transform(transfer_values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数组现在有3000个样本，每个样本两个值。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3000, 2)"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transfer_values_reduced.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "帮助函数用来绘制降维后的transfer-values。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_scatter(values, cls):\n",
    "    # Create a color-map with a different color for each class.\n",
    "    import matplotlib.cm as cm\n",
    "    cmap = cm.rainbow(np.linspace(0.0, 1.0, num_classes))\n",
    "\n",
    "    # Get the color for each sample.\n",
    "    colors = cmap[cls]\n",
    "\n",
    "    # Extract the x- and y-values.\n",
    "    x = values[:, 0]\n",
    "    y = values[:, 1]\n",
    "\n",
    "    # Plot it.\n",
    "    plt.scatter(x, y, color=colors)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "画出用PCA降维后的transfer-values。用10种不同的颜色来表示CIFAR-10数据集中不同的类别。颜色各自组合在一起，但有很多重叠部分。这可能是因为PCA无法正确地分离transfer-values。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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L8Z3aWtZHwpyTt4OJjlqq4vmdHdiZpp3OYO3wyBtw4WAbv1iWfFwTcFKhTo5D4A/0Pujg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\n/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mUqxOJ78MaemVxYuDeNP4BOZoZxcnHYSphe9r8M+w8SjQ1js+TzglXFTw8TT9xRxYxI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kxBwStLwNo53whQor3T9SsL1mwhyAlvkR3rqxkPXXfYdqTx+oZnAnetEO/Bf01RlcDUJoVBds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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe0fa32efd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_scatter(transfer_values_reduced, cls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## transfer-values的t-SNE分析结果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "另一种降维的方法是t-SNE。不幸的是，t-SNE很慢，因此我们先用PCA将维度从2048减少到50。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "pca = PCA(n_components=50)\n",
    "transfer_values_50d = pca.fit_transform(transfer_values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建一个新的t-SNE对象，用来做最后的降维工作，将目标维度设为2维。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tsne = TSNE(n_components=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "用t-SNE执行最终的降维。目前在scikit-learn中实现的t-SNE可能无法处理很多样本的数据，所以如果你用整个训练集的话，程序可能会崩溃。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "transfer_values_reduced = tsne.fit_transform(transfer_values_50d) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "确保数组有3000份样本,每个样本有两个transfer-values。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3000, 2)"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "transfer_values_reduced.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "画出用t-SNE降低至二维的transfer-values，相比上面PCA的结果，它有更好的分离度。\n",
    "\n",
    "这意味着由Inception模型得到的transfer-values似乎包含了足够多的信息，可以对CIFAR-10图像进行分类，然而还是有一些重叠部分，说明分离并不完美。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kSSNe/oeruDt4M4fK9zHN0YYQkvRMP1ded5C5CxpwpQwdF5Nf1EH/qJCWplR2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AB2ylpqGMNafQO75G6kWXJTWTFPBxx0hK0EYmaimgmBpMAR4vI8FUeG1skRHHiMEIihQgi44Hr4\nylVGAagsl6EE2YWrfmD8f9sV/eWovwwMRh5MFqMmxhfSFw2OSZiBo2l8nbocUhZIibBzpTKGJ/Wd\nw/aIr6eDzZqXH6uHUC2yULuC3TNsUI8ZpbxNCSmIf/8MPvqtMdzrCox/zkJehcq6k6L483oaVQXM\nyFcpae3oRx7AsEKYYzrlxRcOmIUBMPVSmHgubFoAgSaj6mhZVwKDM7PrGAjjcxSaw3FSmjpsGi/5\nfHwtQ9OyIlTOGT+b8rw4962PsKJFo8iu8LVxFq4Zn1lkva7H8YWGkE6CSrH7JOy2Udito1AUE5N6\nteUNbKS26a1eolnG9yFljNqGJ5hU/eOUMRlmUw5jy6/H07mS1o7P2GwzsSmrjF22/OQdheC9wEbe\n7JxCS6znC3nX6uXB4mbGmfoTxCPsdsaYzczd0+VLS7Z+tcaTGeHOWIxr6ut5vaKCApMJn/QjEP1S\ncYUApxLHhpUww7cotudmLkjVhcaIk0JLEFUYhDGoh1jIW3hlkKgUWIUG6m6+kqXyTGhqgjzoFDpD\nVLp9bFTCQPWQzxuTEl1KrCPkY7/ioCAQQojvAD8ASoA1wP9IKVd8ub0aBHYnTJiefvvUw2HH+oNn\n9Z8Kx59jlAI/4EWNEu1/9UdQniBbM441qoH21ZkQwCFHDqn1E5VSpohclslWNugetjG45HHtjlwC\nfguFxQEKiwNoQvKStpvvm6ZgyTLM/Tve7ilPMhDyJ4A1MZZ698JHv+u6FIGiS8asNjF6jYkZb1l5\n8ccBGsf2NDq3zIQvOpZ4ZwemPmt8KQTOshMRiWyGba8bbTeuAbsbxp8JJ93Zo1ZpssG0ywbv73Dw\nnclWPmrqezMkCMgqCbMjNvSc/lkFJp44IbMhSErJKt9unvKF2KFZGIeHq2VsUOdVln0CbtdMsh3j\nUpKwSKyd2vrHB6yCKWWMNu9SCnKPTrndpDoodB+L7o3zemF6ArTZW0BrPNkVVRdxcVtLK/8qLaJN\n03jL7yeg6xxqs+ESglWRSMahmDpG8bQXfT6+5XaTK3KQuuzP+aTEFo8xXSthua05oZ8iE9E9ghxc\ndOBNqwEiJUgEUlEQibxbUyxGfIDAxrgUrOgs42NvBW5TmEuKN+BUY3hllAWeQtb7i9Aw3DNH5+5l\noqOVyfZmPoxUI1FoDjhoDjgoskfZXRCjKsMgyqZ4nD+0tfF2IIAGHGq1ckt+PrNs/wXp+F8AvnQC\nIYS4BLgH+BawHLgJeEsIMV5KmV4Y/WDHvMvh3y+Az/sFFKNKg4JSo8pl33LfQoC7EFrrEwGPB9jN\nMmYSfOe3PeQB4Jyvw8dvGiqTXfdHUaCkCk48b0jNr2yN889tkvpgHlPcBZw6uY33TXtJNfRKHRrq\nslm9bBQosGVjEUXFPo48fg8b1Z46CKffD387CkJt/auK90XuaCMTIqcCdr5DcrZqV769Dqao5ORH\n7Txxlx+E4cr4SoWZKeXnId9YiZQiYcoHhIIwWWGiUX11zT/hpa/SzcWinYZY1Kf/J/nKg4LZ1w3p\nlg0Z88rNVNeE2L3ThtSNa1LMktxxfkx2nTKTCSl1vP71dPhWI5HkZh1Kbvb0Qa0ngyEW8/Fs3Zv8\nTp8BmJFIbuDDjLIVHPZyXM70YmT7ml7IqMaGL7g9LYHoQnHhNKrbPmCPuzBJsVToOo5YlPdilcg+\n90IiWB+yMd/r5e62tm6Hw+d5I7dFjfd9rBjNp3I5cURyTJYQlHV6cOhmznOezWZ9Gz78uMhmglJD\nnDivxd9CQ3bJoCShPWbnzfaxRHWVcwu34DaHiZvNVOxrZG95Tzn5oKbycstETEKnKZpFRBrTTUfc\nxuL2ar5a0Mb9zS5qIza6KtB0albeaBuHLgVjbB182NNpAJpDFi7ct4/ny8sHJRF+XeeK+nqa4/Hu\n+7ouEuHa+nqeKCtj2giJ+Nw4GOw5NwH/J6X8p5RyM3A9EARSRCv+ByG3AH7zlJFtYP4Sim4BtDZA\nLNbnQ2H8uIthw4ovJkajvtYInuyNglL47TNw/NmQ7TYUKb9yFfx6/pCCPx/bGubkNwI8uSPKu/Vx\nHtwY5ZYF2VzbMZsblUnUkI25q753p8rWzQUs/7gCKQQyMTo2N2WxZW0hll6vQ14NfGcjnPhryB5E\nUnrnO/DXWdCxh56y3CmgSEFBnYq7wTjPVdVmxmgqMm8sYu5PEDm95HkLauDU28GRhxaDtxOesb4z\ni4wLXrsedmUedwoYYkXvBQKsDIfRMnwGbp1sp/iwdvKndJI/1UvxHA92txHHcW6WnR11f6WuZQGB\ncC3B8G7qW19h294H0PXhS6FHYx1s3vsQf9YnoSPQUTiUBkbRmRGBMKnpAz8i0VbC0Xoyma5FJkOl\ns4BvtMTIioRASlRdQ0iJWdc4tKUDbQAtkv9ta6OLyvfvTepPU/cT3CaN3fpeGmUTrojRhy4ouk6F\np5WCgB9FmMgRLg5XZ3GyejyHqTOx+4Kor/2Bcxe+w8Rtu3B3dFLmg32NJcxvmMo/6g/lscZDaYxm\n44nbebFloiH+pevkdPrI9hkFshQUGoKV1Eez2RPJ7SYPxtUItoXyyYoexa6IHZn0TRoMeYm3gmgq\n6VcEQSn5qyd9VdAuPNbRQUMv8gCGlUYCf+kjJz6C4eFLtUAIIczALKA7mVpKKYUQ7wJDs2MfjCga\nZQRXghEP8f2zIJJ5xPr+Qd+BRxqkYce6lHsfEIRDpBTPLyqH6+8Y8NBAMyy7H7a/AWYnTLsCZlwL\nqhnatn/KD5eNBkxoCTKgSQhpcPMnYT44M4/yHXm8+k2ofV8ScUg6Z8XYekUYPYmjCPYuLebC+0po\n/qkRRxDxwfSvgc0NvrqBL09qEGqHf50HjasGvx0l21UOe8VK3lIzd0tDzvqUuw9h3Fn3QLDdyOSx\n98QTtGyEYP/Cjj3nVySLHohxyAYLn/zJsIYUToRjfmKUOwejIFhtLIZMmLjnd3Z2D6ylqsq9xcUc\nMsiK7FKXi32xGPPVzm7bTrai8IeiIhTfx0Si/WN+YnEPdS0vU1GcmXa2X9d50++nIR6nxmxijOdx\nanHioecLG4W3O1gxPQSKsOByTkq7R6oiYemQ5Rg76D5SSkomX8Rduz5gmX8t9VYz+Vg40j2DjaUT\noS79+QamBz1ZCV3BphZEyugFicTm+JhFemKrzZw43Hj/Cn0dlPo6EEBO1pSkY9cFfBS++UsKIp2Y\n0DlyZc8Ysa7qdJrLkxcBEkFH3M6eSA7VFg9SUaip3cuaaZO5SJzNLfrytM5RHcH6cDxNEqzAr1lZ\nFyjuf2ACL/v9bIpGmWyxcG52NrP7lKZfEw7zf2lIggasykBvYgSD48t2YRRgZCr1HXmagAlffHcO\nIPKK4YE34a+3w7pPIB4zymVf8l34v9sNV8N+xQGKa7DY0gdApuyGAuMOAX8HvPIPWPauQSSOOAXO\nugay0wfeddbBo4dJ/I0SqRtDzZ4PBVvme7jsmXreWvoRMfrX0dAlrPPorFmu89pchZjfcCXYgoKp\nH1qZtMTCgh8G2De5Z20ScUgCz2Tx56d7kvyW/gFMGQYgSi0z8gBw2qPJFpaWjfDUGXDirwVzbsjH\n3kd525xaP6obQhfsW6dTt6Dns8bP4PlLYNkDUPlMkD9oreyLp7YENGka32xo4O3KSnIGyKRQhOCH\nBQVcnZvLqnAYhxAc5XBgEYLNLekv3jdAQa7eWBMO862GBvxSYgKmUsdP6UCQfEOayB7UHqAIC5Ul\nl6Eq6YucWS1FCKEiBwl0UZVs3Nkz0m7f4NH45aoQ/67XjLgBMR1r7mROmSj5VaUbl8XCEcChtp2s\nDcukFbcAKlSVPdrgbs5ii58Cc4h8c5AfZc/g+U6dx73e7gnYKjTm5W8j12yQh5iusC/iotrWYZxT\nQlNOHp12J0VxG06Hi2ypowiFkK7z3IZF3BFJPeleW/cBj486JqXeijduRdoURtU34XNlc4ZyKmZh\npszq62Nd6IKk0CQNt1eaaxVINgb6K5n2tABbolG2RKMs8Pv5ek4ON+Xl8YLPx5NeL9tjsQFjR3JG\ngin3C75sApEOg85+N910Ezk5ybWOL7vsMi677ABFkQ0Hup4siJSTB7fe33+/Hz8EP7l0/523q1ro\ngUB0KFHbwvgmz74Wfna54VLpCip99TFYtgjuegqcqaO5P/gN+Bt1pN41qRn3cvuSPLbev4DYNDMD\nFQVa8UtBLND/c1UXnHOPk0f/5COSJREalG1VkbL/oBJPcfwBgYTFtxmFro77ORRNMQpsjT4J8sZB\n0TRoWid76VD0OlTVCY8JYt/e34KwrjXCvYHGAd90HQhIyUK/nytyBq8fXmIy8ZWsZNeA1Pu6ynpf\nmqFRkDqIsY1QeB9SsfM/rRaCCXN7HCilk5gQOBwa88zbaNEcbAwUsVofRQtO8gj2y16xWyvIc83G\n5ZyYVowqEmvHF9gCSHKyptPhW5mm5wou52RK8k9GVe1IKdnYoRPRJFPdKhZVsL1T49Q3/QS7uZkx\nUUc8FhZ+AusiTbw+voQys5m/FFdxW0szi4KhROtwTlYWmyIRyIBAjLN7ODzHMIe51Bn8ID+fq3Jy\nWBEKERMBmi2Lu7UdNClY1F7NvIKdXb3qRtBsZbdFslv/iBxcfEU9mUVBjdJAEzGhYE4xduTHA2Rr\nETpN/dlsvilI5d56RjW1otVcgkkxMlCmWU0stXawN5LTi0gY7+u33DZOdWTx2/Z2ojI5XFMBnELg\nSxWAkQZ/83ppiMd5PTD4CyuAC/5LtCSefvppnn766aTPvF5vmr2Hji+bQLRiWJT62qqK6G+VSMJ9\n993HzJkzD1S/hg9dh7eehoWPQWujEazoyuuZPCvGwkU3wCFH9Ryz6IWhnycYg62t0OgHkwLVuTAm\nz1CKOQDkwZObw+tnz6MjN5sb7n80M7nd8YfApd+DjSuSyQMYvzftgXeehXO/kfLwTc9qvchDDxQR\nZ8vHYzhx2rOJJLXk3ggklU6F+j4Bjb1hisGET8ysO8kIODtiwcERUKVFDCLRBdUCc38H5z4Gfz1O\nRwYMktNFJCQSpCAyy4/97f4KUVuv8Sb2GxiKButrY8hDhheuY7WUEIrsSblNVZz9yIMuNaOKqn8t\nAKspo41k7Y8Ok511xVXEFJUptKAjODpnHwtaJnJX5CRu4X3K6cmecNrGUFly2YAl3BvbF/OOtovV\nWRX4VSsFMYXjxGSqfLXoMoiiWMlzHUZh7rEIYeru97LmONcvCVLrN+5knlXwm1k2ljbHCac07AiQ\nkqZdNh4v9vKTggJcqsr9JaU0xeM0xONUJIIAj9+9e8B729XeJEcLSLALG7kYRK/YZOLM7Gx26u28\n1+v92hbMo8gaRJNGunA6dOLjY205TfFDqbe5MaUZOyLCRFBNDloUSIotfua07eCkj1cjcsoxVfWM\na4epM2gpfI8l3grW+ouIShMF5iBn5QS5LOswhBDcV1zM95uaiElDQE0Dxlks/LWkhN+2tvJm2rog\nyVAhI/IAUGM289X/EjXLVIvqVatWMWvWrP3S/pdKIKSUMSHESmAu8AqAMN7YuUCKpfp/AJ75E7z8\n956/PS3GTxe2roE7r4OrfwhnXGUIT7373NDOEYjCuzsgqvXMDO0haPDB0VWkl5AbHryubH5832/Q\nVYWCltbMtfp/9JCh0Dn/7pTprFJKOla+w5azz2aGyO9f8EqLkVyepxfiOpW08z3e4o+cjoKOjoKK\nhkTht7PtrBigp1JAdrugaJfKMc/aKNs+yKvQ2ybW9XtXmcIDGIeqReHtm+GyhXDZ9jCP3hLA/mI+\nImzcF70ohueBnbh+XZHyeM+UKDKDt1wTsO8PZv5ZZ5zLMkTtCE/2yRD5J2a0bqtAl20oVSGwFs/7\n3eQBwEd/V0N1ficxRe1mNIbguc65BZv5tK6IzsQxJpOLotwTcbsGSKsGfMFt/Es0szY3kZUhBM0W\nF89Zc7jMUcOJtkkowtJP72FRfYyLFwWTTOLtEckNH4dQRSoffhcE4Q4zy0PJWdd753QAACAASURB\nVB7FJhPFJuNL2RKJZPD4SHLUMFmmKBI4VMxEItgdi2EVghKTEQzZG7XhXKptHSnfgN5cTiLZzT5q\nLIfyl4Jp3FL7OtnxcJJlRwKK1DijYw2vumegJyyBVdYObgi8z6mfrkKpPgZmXWmI6SUwSinlbPNc\nKt3rOCl3NWYsTFbHMU3M7iZmxzscLK6s5HW/n3ZNY4rVynEOB6oQ3F1cTI3Hw0MdHYPeo6G8gnPt\n9nSjygiGiC/bAgFwL/B4gkh0pXE6gMe+zE4NCy31hp8/Ezxxj1H34akh1GHuwvrmZPLQhQY/NPqg\nbOgCL+mgCcHtd/2MuEkFRaGtIJ+w1YItkoH41PZ1MP0Yo3BWCq+UFIJGk8Yj+jYc7ORGdTLjeg2E\nk4+vZ+Wrlcg+M6AuTUwofReAX7CAydTxKCdQj5tD2cP3jh6H7aNclg9gFVakYOYbZuYs7G15SO8O\nKZsN9SsM79D4s2DsabDnA4hHoHg6vP/LwW/HcCFUWH4/XPmWk6vnR/nn31bjW2UGCa6Zcb6pjGHh\nNU5SOREcdSY6xw1MIkQczH6Fypez2R2Cf98G8+7LvH+fhEJ8szVGCadzEWuZSR0aCiuVco50j8Ht\nSo4fkFLS3rk86bMakjO2c9QwZdYAfb8PIcCi6lzr2Mz03HOxmN2oij2jVNFPvCtZW5hMtKQwLAWv\nmDo5UVj7tbPbp3P54mBakqANMnMJReIcwN9ebjZjE4Jw2kwY45k8Kmcfe8I5LO8cRb01m8WBPTQl\n3B7TrFZ+XViIS8mmM6GBogpJY9TJhAwVJ6fbVCrs2Vw/+Vr+uHk+JVHDsqMDmwqmUOrZyZ0bn+d7\nljdZUzoG1azzVN5xHFV9HdExZrbGdeyKQk0fV1WJKGKeaWBV2VxV5fI0rrOFgUBG0VxDsbn+pbOT\n+T4fdxUVcYLDgelgKDvwH4ovnUBIKZ8VQhQAd2C4Mj4DTpNSDhB3fpDiL7/IPC1S12DxixDyD/08\ndZ2p3ygB1O9fArFz3Bg63T3mPs1k4pXzzuDiZxYMcFQCbzxpEIijToeta/ttFlKy4gjDlBZC435t\nI3erPaW3j7ungK3vtuILFSKlikBDojK+bDETDmmACfMQW97kIpZzEctBMcGR18GYUTx6OQNE0kiy\nHO2gx/FrxfQMP6kHetUC1y4xFCeF2qM4OefbPfs0roStr2UmPDVUSA08u4zfpypufmedRcORIQRQ\ngh1FCORf4KWr+x877gkXDScPbAbOXW/h8FuKsPgVJLD6UTjtHoMsJaGzHtp2GRkixZO6d7ivsQ4k\n1Itc/sRxPfvr8JHq4a8yRpboMX/rMoauJ8fSlOHjaHbxMdVIBFZl4NTPwsLTcKijBtynN/4dCLBR\nMR6GrHiY8oiHuFCpteUTV1QCwkQTIcpIDnB9eFOE2LA9ghJ7QRSTxw6JrgZ0HRN0KyI6FYWrc3L4\na9q0QmNye6N9XPdfz0SSRa82RCJcXV/Pc+Unspg3iBFjvKOVV1smcFzunkEthjZsZAsnj5Q6uN1k\n4rSsHzLLu4vSeJBpZZO5ZNQ4nm1vZtvW9ykOtbLbXMDm0pncUVrB6+Eg97U3EkrEK+SpOje63VyY\nnTcs/Y/1kQjPdnbSEI9TpKrU9ktD3z8ISMn3mpooUFX+t6iIw+2DRCqPICW+dAIBIKV8GHj4y+7H\n54K3DTYsH3y/4UJRoKAMmvcNr97vMKElovIPX7KMeQvfoaSxiZaCfKJmE5bYIPn9n30Ee7bC3Ath\n2TuwaaWhvwAoUrJpykQ+Ot7wmUogiMZqvY0jVEPWN7vGxXXPLmP5j7axvfEYLGqIaVWvcei0jxDX\n/Q3KRsOk06FhnTHLl88CqxHc591N2mWLOUvgD+T1mu0NpmG3dBCK5tD3BmtReOx4uPgFyC5N3eb5\nT8Fb34fPHjeIhskGzuJEPz4nFBMUTe31txCMSkx0uxbDO7dCU39+BkDJhw4O+W0e625t77ZCmIDT\nPnETeNiKa6MVq6d3kTCI+g3vURdRIh6FJQ/CnmU9DdtzYeLphIXKevuUlM+kikaJr4X1kTcZby4l\nxzkFVbWjCDMm1dVP/fEKVrKKUcRQaYs5iOoKljQFn4qV9Cl+qfAXj4cJqoNjPduY5dvdTRUjQuXN\n/CnscBRhTWHY/rg5PnwPlapjcsR5f4ONT8aGuKetjY3RKAow1+HgRwUFlJpMfNftRgEe93oJya5i\napDKxtflOet9V3SM9Nc3fHGuyT2f1fo6HNbdbHW0EtFV7OrArHamcgiKUMhX4YGSEtq0QjxaFeUm\nE7YE0bkkv5jw4ReyJRrlBEWhxmzmzYCPu9o89P7y2zWF21u9PNzeyUOlZUy2ps+C6YsFPh+3tbSk\nSe08MGjTNL7d2MjrFRWUmA6K6fA/CiN3bH+had/QRJlUk6G4+OZTyTES6TBmCnzj5/CTS6AiB3Z5\nUko8MLoQysZAfYb1nQfB6B27OOOl1zn/uVfQhUCRktL6xm73/8BcRsBHr8Pl34fbHoElrxP9dBHr\nZAerZ09nxRGz0Uw9g7bQdbxr3oE5V3R/5jjjFCbMrqalZQ1eRaNVn0V49E04nInUvuwS46cPiqZB\noCWFRUAYgYqGxJ6p50MgFM0lpyr1pL/vE3jmbPjG8tRBhhYnnPUInHoP+JvANcqo6BkPw51DXdz0\nsZzoGhx5S//d1j4JC64cvLmJj+ZSvSCbjrODzLsPjs1y0LhK5bklqfe3ZPUiDwAr58OePuQ41AGr\nn8aEwHTkHcT7BC7mEOIXvENFyIsMCRpYRWPb21SWXEaWfTSFucfQ0PZ60jGvMJUIJizEuY13cXrj\n7HMX9tMQGSfG4BJDi6LfEo0yDskckr9ci9Q4q3Ud75SeQL7JipSSGGDGqLZZYBWDTmiqHjdEopIe\nDMOU37nLiTk7xrca2rq/UkVodKjb+WdkOROwMEap4Hr3eL6Rm0tDPE6eqrIoEOAXrclunUTR+zTl\nsYxrNAkTc9QZzFFncFTBPl6O1aFLLWVYlAULhykzGa8ka1zkqyr5KdJ5bYrCob20Qh7uaEk8qv0b\nb9Z1vlpfz6LKSlwZFFlbHw7z8xZjHPwixf8lRp2MF30+bnC7B91/BMkYIRD7C4VlxgCSKYm4+lbI\nyYev/wzuuXngzInJc+DnjxgCQxd8G4J/MgImQ30sABU5kG/db+QBwBqNcc4LCwHDagBDkC9VlB4X\njckMx5+DetxZzNdW4Ke/9UIqCtULX4SqEwwRLuBjvZm/5zcj8o2l/yfA62zjx3IaxSL9zHz0j2Dn\nu8mfCcVYzWspwzeMQTCtxUBC/afGz6g5KTZLWPl/8PE90LEL3GPh6FthxtfBUQTB5rRd7QdbLoQT\nQnvOYjj9Aajso6KsReHNG4fQZpvKzRdnM66rQOTs9PtG/dC2FfLHA7EwbP836cw5JiTzWtfxRsEh\naErPRPENllEmOxOZvF2FqeLsbfwXE6puxu2ajSYjNHs+AGmYqZdQjY5CGAt3cjKn+bZwiN5EyGVD\nN6vYsDJFmcg0MTnzC0+gQFU5Rtvdj/QaE6DkrKCfx/R1tCnbyVLDdMbt5OnjubKmhvca04u/lQWb\naLLlp2CVAhk37Dplo0PoGBOjSWhcWrSBIouRMdAuoV1vYwe7OFM9jTEWI/X0ApcLVQge8nioj8ex\nCsH52dksC4XYFYv1+zYEUNRnBV2plnOFOJlX9DdJVUu1nJJ+5KE3fNLPJn0r+2Q9YQztl2KKmKZO\npkgUsDdmVAdNDUMxcqHfnzK+oUPTeMHn41Wfj92xWEpryxcFAew9QK6S/98xoqaxv+AuhMNPSdZ9\nAEPVKKpBJA7RODQH4MzvGrUyAObMhd88AaVV6dv+ypUGeQC44DooK4dTa2BKERQ4oDQLjig3fvZL\nSoCA8dMNqelTLkZNUxBsUE+KrhkiUr1gEgpn+vpLVSuaxtitOxi/eSusN0zlPhnjMX07EroHYAn4\ntBgP1u4gNICa7Zi5cO4/wdpr7HKPheN+MVinB0bjGnjnR/DHKrinDBZeD949sPgX8Nq3wbPDsHq0\nb4NXvwkf3glTLhraOcIeOPdx+OYKuHlf6uMbVhvql0NBtJfHwLNj4H1bNiZ+ifgMQYoB8IPa1xkV\n8XTLN7v0IHPYm6i42BsSXUboDG5BCEFh7jFMqrqVp6zncSPn4qNndRvCwktM447AydzbcAxb2k/m\nctOFHKpMRUkhZjQYLs3JoYBAkhqBHwtxBAqCNYoH3bqWXFMQs6LjNgcQttXsy1/HN8Yb8Ruq6P/M\nf2P3C2gDpI1KQM3ukVM+JKuZIksA0VWeItGgBy+bZHJ10XOzs3m7ooKlVVUsq67mtoICrszJSfmG\na4BH01jk9xPttYjJU9yMFdUp+7aTPazWUivStshWFmgLWS830YGXMBHCRNjNXhbG3+ZPnt3d6q8D\nYW2kv25MXSzGufv2cW97O9u+ZPIAxneUaXGuESRjhEDsT1z3KyNosDc6QvDuTnh1K7y0GU66Bq7q\nU/moZhr85kkoq+5ZyXQNkkecCrNO6NlXUeC7d4LTYRCIk8bAsdVQmbv/6m0oCkycAVUT4IShFbbq\nh0d+DR8uTPro5JibS+c/S5bPsE4omsZhH6/g+3940BhPzcYqbLVsQ0tVGUCF+govfzwyRuvm1Kft\nrIMPfwMRrxH4CMaEW344iM9hd/voTlh6j0Ea/A2w6lF4YJxxLqNzyf9/cCcc9QPD8jEUrPizkfmR\n7jh1GOOdvVeF6ZzKgfeNF8dZ4PPxSlxFmgbWyCiM+Xnxs/u5Y/uLnN2ymiualw4wsAg0rSeoUwgT\nc4tLKCjQcJqjpCLAGnCS4/PVJL8mJwe/twBNEyyihhs4n2u5hK9xKY8yh1ZHQl8j8Qp1mfyttq3c\nPEvhgzOy+OEhVn58qJXnTnJwQolKbrST05qWDnjeH0yzUNjLTTfOnj4rYou+HW9UstGj4Y3KRH8E\nLlXFnOjYRdnZXO5KHST9it/Pjc3NnLh7Nyt7STXvkfvSnnONXI/Wy88XlCE2aJt5V3ufeBpnySed\npfzVo6FnEIxVpKr9aq38b1sbbRkIZ30RUKDbujOCoWPEhbE/4cgytA/qd8HeHYZbozMKb7wBJhOc\nfz6MTWMyzMqBu56BxQuM4EOrDY6cZ0g+97VqTD0c7n4RfnVNZvETQ4WuGemooSD406iWCcUYbQer\nNBoNw0M/hYoaqJ5oHFpUzilbGjjxf35MR44Lpz+APZxYqZgtMNOI5I8khqh0NpVQROfVb8I1H/bf\n9tJXoT2xyu4aH8MeWHA1nHB7slhTplCt0NEnOFNqqUUEvfk6y88Js3NGnCeWwCXftKP8OfNZv26Q\neNyS6QYJ8KbWbuoHc2L+7QonyB8H1SfB7vdTZY5InjtWpfE4hc9+5qeh5Ci+te/fA04Xdj3GBc2f\nMiVQx16rG1lsRohUZmHJv4JOFnfuxaGqNOhh6qISSK+AebTdzlznwARClxJlAAKt+QU7bzue1Q+s\n4m8cTteXGMXEO4xna1sH5xdu7sfBLYrOZ9FmTs+rZFpeDxG4cWmILC3IZP8uZnRsYq1rXJIlQtXj\nVIYa+cGUccxs3YQjvhYHMdZTjp4iWFNK2B3QqHnNS1wXqEJy0VjBvXNc2E09nVKE4GeJ4Mt72lOb\noLy6zrcbGlhUVUW2ohBNmeCbuG/otNBGCUWs1zaxQq4a1IbpjWciumY4i/7m9fKY18spTie35OdT\noKr8O5g+LfaLRrGq8vvi4n7unxFkhhELxIFA2Wg4/GQYMxmmT4ef/ARuvTU9eeiC3Wm4K376F7jl\nj3DUvB7XRV+UVsEF1w/cXhfxGIbJFzBUIj95K8UGYWg75PcPXkwJofQXy7ruV5hMNgraO7BHosZ1\nCgHX3d4tbT1JpDbXooO6y4qy28Kej8BXn7zZuxd2LQLZx/IudcNq4CyCI29lyNkssvufwbH0/DAb\nj40RypE06ZKHjgzSeMQQ/Kw6zD8F6lak3iwUOOcfRvJJWvS6vngY5p8ML1/TE25zwVNQ2k/M1Rj4\nFU1QttjJ6adW8Nai8/hH2bHoA5hR2oumcvWsm7lg+o18f9JV/F30rx3hw8rvOYGHQnY2xmJ8Gg5T\nF+3qaO8fA1UmE78oKODBkpKUufoxXfKHtWHGP9dJ/hOdHP6Kj+d2pTaIb38D9rw9nidDXQEsPe1J\nBLVhN43R1JU7s/pIYi9rbKEhJKmzFbHXVszfVv2S8pAR5KIm3D1FEQ8PbbybfS1PURH6hAKCOIhR\nEWrvjgnpi6Xbq4gnSqVrUvCv7ZKzlmxjs741yUoA8HEwmPbxlUBQSt7w+2mSzcjBHlopeT++hOUZ\nkAcpM31tevbSgHcCAa6oq8MTjx805KHMZOLtykpmjZT1HjZGaNd/Mk46H9Z8DCsWJRTgpLEcPv5s\nmH2ioXLZ2gDlNcY+Q4ZMozch4M6n4R+/hZZBSlWCYaXou9/oSfDHV2HR87B7q1Fs7KTzobKnOFa5\ncHKkKGSp3tKTvxY3/nf/cDQi4YPd+hpsfM4I/CucAuPPHLg7C781eJdTXkaGZUB0IalabyLolngL\ndbzFOhPeM1H8ydBet53vGj/nzYdDUmRbjD4Jvr0ePvkjbHoRQm0GDxt7OqDDlpd79u2af9Y8DjWn\nw9RLIKsYvrEM6pYZ4lG7FkvQ+0wPOhx6ZxEvOS5h19Vn8Gs8sHEhNG0wtisqjDuFm0edyme9/N1v\nMR4dhUtZRzYB4lj4EWfSip3MpiCJVYFL+pjrG+NxXvT5qI3FWL7ezNo6pfsR3ebV+NZHId7xBsgv\ni1Ggqpyfnc1oi4VoAALlMcL2dGRaUh/JotTao8uiS/BrNo6yFHV/FgzX8ed1tcBkpFC4fdK3+dvq\n2/nkvctZVHQkW7OqqA7WcXrjh3i++lXaw7uTrrbI38me3ILkM0to6Mjmo23VfXokWLmniFc7/82U\nrD2cpp6ImvDH+eTAtEAFmuJxPtU+G2AvA016KzuoHXS/LtSGhy4DrQEtmsbzPh/TrdakZ+XLQpai\nDGi1GsHgGCEQBzvCQWjYDS53/xW/aoKb7zWqe65cDJoONruR8RCNwA8fBIvVGKFuOMUoKb4/IHWj\nX4fNNepcpIJZNeaJqGZMMuU1/ffJLRjUinKNMg7Ly27WPykQEQWtPIJpkwP7B4bJ25pjEAKhGpNk\n5z7Y/rqxMk+dbXHgISRMXGpm0lJj5dpeHMfdpKYshJUJFl4PE89LLS+dWwV7l0Cg0fhbj8GWATS+\nhAJr5xsEAgwuWH4E+BvpTx4wam5IJJP/6GbnlVGonAnlMyHQBiEPZJewXVhYsa+vn13wDuN4lxpe\nLStgWUTS2jaUqE9BQzx51f1pKMS3GhuJSUksqNBUl5x215VO+PwmKMvyoyjwmNfLXYWFHHtiNrzq\nRUhpqE+mOJ+q6Oi9ZuW4VJjNbNReLsSm9rdpjUyniwS9OOpkQqqFW7c9zrymJczu2ECnyYmpsoa3\nJ+YyU3qTzLyqlDiiEYIWa3fARYvPyQPvHk00nmo4FjR6s8nPamKnrGWcMKyYR9ntbBhABjsO1FjM\nNDC4i3M9GwfdpzfMQkNBZhQD0RsSeLijIyOzdybqk58XR46IR31ujBCIgxENuw2T/6oPoGkvaAlb\n/LQj4IY7Ia9nRYSiwKFHGfEXd10HwQCoqnFMfgn88u9QXGFkbzxyx/7rY14xVE8wAiR3buhJX3VZ\nYWop5CUyLbwh2NQCp14yrNN8cLtg1x2FOPuOKIm/44kMu64V9vCUIAdXtBgK+hKFvCbT4GbkARAL\nGC6ZCWf337ZmPjStybwtqRuBpX0xkCtEILC3mJjUboeu4EtnvvED7BugiJFEUKebWRMZquKqxNmr\nNoomJT9sbiYmJToQ7kwfTyLjCtGwitlhPAw/b2nhvSoHR121jHA7fOCekJRyKqSOXY9hV6O0xBxI\nKZAIjrVWcoylJztK12MEw3sY5yxjqae6ewJ9o/hYFhUewQT/Lr7a+h5fP3YMj049mnj0XVKFgZR3\ntrO1sKynXSnSkAcDOXYjIHK3vo9xibTLy10unu/0EjVF8EeTvzwVwzw/yd5JQwaPXWQIeRBCwJkF\n23ileTod+vCe6cFcGCow1mxmW4p01f2Jx71eVoRCjLNY6NR1xlksXORyUTYSD5ExRmIgDjZ89hHc\nci689k8jGFPrceTL9SvQbr+ODf/SeOXrOq/NW0/tWd9HXjEbfn4lBP0YbozEMZ4WuP/HsGEFFJTC\nFTdB1uesQqeoMONYKCgBi80gKFf9AEZPBrsZjqyG3F7M3mWDwyrAMvShoHk9fNDFeRIBCGXu9Ywr\nfZ/C0iaOvz29lSFz64PRr3Pm/JQTp96PqgzftDpQqMlwrQ9dSBeruvpvQ2tHKBL38RrN8eQAkYqj\n0xzQdX4huXhU6hiB0ZaBAjHALASN8UFUS/tBcEgv3/TaSIQmTesRHTcN/Dwpas/2GLAoEKC6fC+3\n7XyZqrAh0GTSNYSU2PQ4D2yajzPqoMqiMc1q4zL7oRxn6hPHkci7PKdkHTY1hpLojd0ZpXB0kPqx\no5hyw00w90LejsdYSkXKbz03FKTQ58WWSFstyfFTVdCOIpKnVkXolLs7GOU28m97k1C3qvCVUQGm\nFLdRkdOJ2uvYWTYrfy0r4H2ZIrp4P+B06wTerqziVwUFB6Qo1Q1uNyUm0wG3QABsjEZ52e9ncTDI\nox0dnLV3L5/1ymAZwcAYoVoHE+IxI2NBi6PpJtQ+9QDiMTNPPH0bex5QURQN5EQ+lX9k9thn+MrM\nO/tnceoabF8Ld1xr/G21wSU3Qn4x3JdC2jATjJ1iWEG6YLXDGVeD2QofPwKqklwNNCGutePu5/FP\nvJlDrsw823TDc0bKpYxDfvYuLj7q+xTlGCJZulTwRc/lQ3Ebuvw8OdyGKeODjd/mO6efSUnuFp7+\n6EGGY5FQrT0Wkf0J1QqjT0y9LZZZBWMDiiScr3HH2fuI7NGZabVyR2Ehoy0W5twAKx5MfZhEkn1K\njPGFqYlCldnMcXY7H4VCSatLBagwmbi2oWEInezBNb0EiMJ9tEhUq4ai6Oh6cuAlSCyuOKq1Z38B\nhKQk21lAUbSTBavv5728iWzKKqMo2sm8lrXYiFO04l3GVB4JE05OmT+rCBNZjnHANh6c+jz37DqO\nsdNbUct6yn7/Q6ujSJuCGcGnsXK2ZBUzwd+UNBlGVBNmRzWXqvPoxIcZM1lHr+EX75lp8vakE7qc\nYa4+ZmX3+1Kl9BQCWy5b2S68CGBUToDS7AChuAmzonOuZRQdcle/wMvhIJssfBjWIycOjlIOo0Ix\nRN4udLlYGQ7zmt+fVh1TJb1yZiocZ7dzXW4ut7e2DvnYzwsdiErJbS0tvFpePqxaHv9tGLFAHEzY\n8hl0etB1pR95AFi69Wr2tholi3VdRU8UN/h0x6XsaBxkCQkQ+X/snXd4HNXV/z93ZvuuVr0Xy5J7\n7wYb2xhTTAumBQgtL4EQEkIaCSGBkDeQBkkgJAFSgIQWiumh2MGmY2Pcu9wlWVbv23dn7u+PWWm1\n2l1JBhPI79X3efxYOztz596Z2bnnnvM93xOAR+6E1544+r4JATffD7c/ZvAx4tr1G3VAMmzJS4kr\ngsyMg7xwhVG3IQ66BtVVRs0MXTdCIQd2wvYPEb4u0EFRwlyx6Gpy0qr7NKnj3vcc3zn7FMYUru7f\nKBbT0bjMBe3eUjyBXMYUvUNxVorCEoPg0zAeImbJ3Lt0rOkSfxusvhXumwT3T4W3b4eyBUNrR1ck\nh77g4d/P1RHMMSbXLdEiTJ2aRu54GHmaRCaIP0HYqXPwt+0cCqV269yZn88iR0wgTAATLBaqIxGQ\nkLXFirsq0dCziAjWfmmGAvh+VlacB2KKzYYt+kIPdpho2ZaO3RzCpOgIZHT1LlEsOhmj4u+9BOba\n7ZSPPIWIoqKgc3LbTr5Z8wYXNawjTQuyrXAE5c37kBsegzd/nbT8PEBB9mmgOrCLTq5yvoq5UI2b\naEJKmDsi2zjd6QQEd/oX8XbmKJpcblodLg5l5vJuzmgWmBaxORjiQ69KS8TMIscMcqZ4yZnYSXql\nh+yJndin+FkbKEZKyCM3ThBqg94aZzYpCjgtESwmnY/0lgG1H/qjUoxkrjITU7/1ZBaZLFYXcIl6\nPher5/JFdVmv8dCDb2VlkaOqvRNJz/8XpaXxcEEBl6bQrEgGAfw4JwchBOenpf1HjYce6MDBcJgD\nw8qUQ8KwB+LzhLDxgm7oGEOu+yBmU7w7fcuhLySVjhUiwvaa0xlVmKK4QX/s3nD0fXNnGWGVx++G\nsdPhzMuNVFKfB267Emr2EJ5SgZqhoKjxL1+pQ2ebwTxf8zuY/XXIrAA2vWMITbVGGYAZOUaIJEr2\nXKiYYfzVNHVW4nYkakELwGlt5ZIF32L5B3ey4/DpKCICSC44/vus2Px9WrsrhjxEsxpA1xXK89ZT\n1zb16K/RMUTALnnnS372LgrzR6D0WcGcJ2yUvWTp5Xk0DdXOUeCd547QMjkY5yHQgHZd50WPhyvS\n0/niU4IXviypelGCNMiTAoHZpyCvTeMXBUFGvWsGTVDwpQh13+lii9VPmqJwjsvFvfn5NEQirPb5\neLG7m+2hEM5qE/O/lk/GHqO4RldliG3fbUM/o4mZmXWMdrQhgL2+TA55x7DYns2ZdjslmocD7X7e\nbFKwmwSnl5j4ZmYmd7a20bHfBRK8QRtnTduBlAqdfhuKQ2OPLQNVja/P8AWXi0qToL7jLWomj2f6\njiqskTASgYJkb24h5W2N0V+WhPqtULcJSmcmXEqLKZP96SM46Y7f8f17fo7sp9GiCEDVMFkDTLOZ\n2BwQ/Kn9OHLMXtLUMKaAxjdsOXzxSFtcpclSk4ku3YwlI4Klj8z7bl8u57gyWGyv6M3AANAHYNXo\nSLwMzTWlIEgnjQbZhNZvym6ng1e1lSxTz0xZe6TAZOK5khKe6epiXSBAxo2ldwAAIABJREFUmqJw\nlsvFYocDIQRzHA6qw2He9ie3rgWx4mC35ORQElWEnGKzcUt2Nr9sbUUjRqr8TxXaCg21JMH/cQwb\nEJ8njJlq8ApQ2HjwfGZXPonSpxphKOIgmWtdSiX63aeIzlbYuhaQhrdg1TNwzW1GmujhfQC8/frF\nnPzVFxIOFQpsePPk3s/7VsDspbvgzm8SR3vv6Fc8SA9z4sT72V13IpquoiqJa5Ke8iOnz/gF3f5s\nwpqTQDiN1dtuwGVto9VTEeNI9p4qnjQpRISRuetwWDuRUhAIf7aqdBJJ/egIu06IkchqfZLac/0s\nbYBxawbmHPRHxgjonBRK+uJVgN3RlDpbOlz8vOB//9GJvMptXCYJQgryPjB4LX4EntIwT15ZR0jT\nkUGjjQ/8ft73+7nM7eY3ra1EAKHBoisLcRyJvWbc+y3M+2Y+rq1dZP0xlpUxytHOCPt6ijf6KT70\nNoT9FGImyEJ+zHl8U5j4xRwrN6bl8r1AbCSvbhnPqZP2snRyFXZLhH3eTNZ7imgKOclQ4cvuXC5P\nT6e++UU6PFtxuyRLZv2AszzbOK1tGxY9wtjGOsx9a9EIFVm3kVczx/JMVxfNmsY0q5UFShr7u5uZ\nueMDgmYzoRSVJqWEJ7yt3JU9hs3Bbl7xthJCYZbDzMWucr582EOTFr/CrU3BERHAr5vM/Jpa5ths\nfD87mwlWK1OVTLbqiVruCjBdZGORjXgZ3CUmgY0yuSUqkWjobNd3MU+dk7KNDFXlmsxMrknx/SiL\nJaUBoQBXpafzhbS03jogPbgkPZ2TnU7e9PloikT4S0fHf8QrkaOqjB6E1zMMA8MGxOcJDhdc8i0K\nHv4Nz3zwW9z2esaXvNn7dVnOenYeXkoyI6I871MsJd6LviUidfjzbWBzgq7T5cvj/fcuQcm0sviC\np5BRjQZFkax57Ux2fDivtwnVArzyKMY4Bl5PSAml2ZuTGg89EAJ0aabdOwJPMBspTUa7QmB2GtIY\nJhOEunuPQKCBkEip4LS2c+as25ESNN3EztpTjuqqmGyGUNOxgkAwcquZzAaFtmK9ZyNI+OD8AGPX\nmAclZWaNgsmXQdkJUH4ivFanppykelT4AprkuUNhXjwo8N3qoTNHJ+CC3MMKc160MXq9sTrcdmMb\nIbeOjC6Ie+7gSx4PR8JhNKOrFLxjx1WbGLYQusD7cCUZv9yEkmb0SRFgJUK5qEKEjcnGTphrWU0e\nXVwjr+aHHwb520IbYBg8QpEodp2VVaNYuX00VnOEZTO2c/FIQ6MijxzOMo0mEvHQ4dlKz/PrVkM8\nnn4c1+9aQZqWnDS7MRThB01NvSve6lCY56WHCl8nE+s17iu4ABnSEZZkHkFoD6t8raGBZwpKOdOe\njcts3K/VXi/1Wv80GEm6GqBbs6IjcKtBgrqJoIwnEq4PBLj8yBGeKS5mnjmPd2mkGm+syieQgZXT\nlCIOyyCt+vqkY4s/c+JK+3AgjU3dBbRH7OSYfXjSupn3CZTEIxgTTbKnTwOuz8pKKhQGkGsy8UW3\nm9+2ppYA/6To692QwE3Z2Sn7M4x4DBsQnzeccRlKbiFL1eU89fTd5Ln3UpC5G38wnb31J6AqIXSp\nRidJY/Wc5aplWvmLgzT8KSFguEp9QYMX8e7L57F1zQmMm7Eeoejs3TyD1oZYyppihrFnA3dVDS6D\njfEydto66PAW4HY0oiSJ0QO8t+srfYwHAAUkhD2AgFC/w8ymABX5ayjP+4hJZa9iN3ehS5UX1v0c\nf+joyvoeS+OhBxJJyW4TbcV9eAcCuvIkQafE5h34BRfsghNvi32+xO3mzta2eNtTN6qan5uWRldI\nctZKD9vadagwetCzb3Opzis3+Djlb3YmvGOm7hQvMsmbQwW2BWNhEleNGSlkr+BXHEIqWr0dJa3X\nqkNISVdafKaHiuQCPuLnnMMhcvl7TYByl0Jrphdnsb9XqDXQbqZrn4OxhS3RSyVwCWPWC0Xa6Gv8\nnsd27mEhr+dM4dzGDZj6G7FS49600T2XyNgUHcL+YCYX2X6CNkJh3J4mxkxsjSMFK5qGT7fQ0Oik\n86CT0Z5uBJLFhWZ+NdvGYSK9FUBH2DoZaWtjfXcxXZqtN+zSrVkRSGwiTKAPQVgHAlLy65YW/lxU\nxPfVyayS9azTm4kgmSGyOEUpwi0sjGM0NRzmCA2J134AbPfksqJtFD0BrJawg92+HMbmeTjVlTwL\nZzDMstn4R2di7rAAxlksfOT306xpTLBaGdVn5e+RHsJESMfNkaNUsLQBQ/lZLrbbadN16iIRxlks\n/E9GBscN60MMGcMGxOcRs5cw9sklXFP0Wz58fjSNHWPIctVyxYlfxWVr5a0dX2Nv66mY1DCTil5g\n0bg/YTF/Cgy+o0BWWg1m1UdYc9DZkseHK8+I+14QQWJi6e8NKWnyiuHw/kGNCCmhy5/PI28/yEXz\nv0V++r6k++yuW9LHeOi/Q+KmUMTJvoYTsJq8CHS8wWy2HDqbTl9x4s6fAQSCkC2x40oYTMHBV0d9\nPeR6BKzXpDNyRoiDF3mMmUgBNSSY/YNcVnWY2f+rADs7+ng74k5q/PfeFwOMfd+UMkHFKFctCEbj\nx90V4eTGA4AtgloU/8xKIXB7ksfup1LDIXI56NP4wkyNF/sxVq0ZYcpmtOC0GgaXRDJOMYwAsyk+\ndXke1fhYw8NlC5nXsZfCYKchLy0UhNSpKlvARvfIpP1oOuBGoiAVwc7tBahmScXotl7VeHNHgK3t\nxbRsT+997iSCtxoinPa6h+uX1CBxsDRrHxNdLWzoKsCjWegvrQ0StylIIJzowXkvEOBgKMRIi4Uz\nKGa2aqNbduMWLtIw9tfQqYsEeae7jMNBN3YlzMlZB3GbUhNhQ7rC6vaR0asn+vQFftbSwmKns7eo\n19FgocPBZKuVHcF4Do4EdoVCXN0QM3IWOxzckmvjI7mWZgyvgxUrbtP0qKjZ4MgRgrvy8rimsTGp\n1wOgRFX5amYm56WlDWdbfAIMGxCfYxR+dxnLWr9kqEr2mWgvWHALnFEF514D+hnw7fvAI2JiTj0o\nKoeGmnhGuUiyHxh1OPz9X97CKFPenkhg7IEEhKJgMQeYP+5h3trxjX576Dis7YwtepMZ416l5LqH\njM2nXQLr3+zfXFKs3XMF7Z4yHljxHPPHPshJk++NnltFVSJ0+goJa0evZx/RbGypPoct1ecc9bGf\nLiRhCxyc0S87QYfx75sxRQZ+4QlTvOjUB7+FquWC2cvzGPu3DJqOC2DyCYpWObB0q9QCj24NoQ1C\n/fC7JZ35kqKVTuqWJnohJDDRYmFdlFPRON9P56gQaQfNKFqfCVJI0q7di+KKvd51CdZIhFEHa5Oe\nuylabCvXrfOmnmhkCAEB1cyhQAYjbd0c6Z7JJd0B2rQDjLNaucA6lwnBdfTM6iezjxMtB9g/6zhc\n3kzSm3aB2Q4jT2Bd2ihkkkJV4W4TeihGZJRSsHVjEVU78nBnBLik/VWenbmY1oNp0dPExqxL6AxL\n1tb6mVHcyUSX4Sk5Ekp+0SUKXVpyjgXAk11dfCvbwb+1t2glxoXIJZuT1UV8EKrlvoZKgroJiWCu\n+zBp6sDiKIeDbsIyubJDu66zPRhk+seoG2ESgr8VFnJtff2gEtZv+3x0tFSzJDt2/YMEyXBuhM4Z\nDCW9ulVK/qexkfNcLl7weHqoPL1QgTpN487WVkZbLHHZPsM4OgyncX6eUVIJv3wSZi6K3x4Jw0sP\nwU8uN0iXP/0HjO6TNZCRAzf82qhXMXsJsR+dgDknw1dvMzIoTGbIK4GrbkluVCBh9kmw9NLkX0db\n1jKKQEoWTvgzSybfjc1suCtNSpBZlU/z7TOX8oW5d1Byap960lOOhy//0OhDD1RTbyEtAE1XWVN1\nJWv3XNZ7tverruaxqtd4Z/fX2bD/Al748A7+9PpL+MMZx1JMMja4PpfuPwGhgmIWjP+DBi7jtD3F\nGCe7VRY8NbB7VZjA6oZFP4ltW39f7G/3AQujnnBT/kIalu7YZBFKERrqD0sYJt2TiblbSZqkf2Hf\nssgKvPNwPW3T+jiTFUn4Uh/tP2pF6+Od8GgWRq07hDUc32gEhQPkspYKhElyStZaulKkWCpAWmQ8\n29sW8lSHSpOmEQF2BoP8NDiG9Wq8MJTLksfxZeeRPnkZLLkZFn4bSmdxUorKn6mcZcGgieZGF4+N\nWopUFMLdJpI9MLoU1LRmckJGTS932Cq0FOtqiVUkP6EWVFjTGOHV8Du00RH3XTOtPKW9wL1t3b3G\nA8BUV+OQ9Vc+DbgUhcYhiInpwBZvNsF+suouNcQpWYnex2TouZrPezz8KjeXy9xuHH0G38PR8UnJ\ndxsbE8qND2PoGPZAfN5RNNIgKiZD7T547XE45yq4/VEj/THgh4LSWBXP7/4OWhqg6TDkl8TqaSy5\nINbOv582alskw5rXYdnVqd3WukBtM3LOhZCcMP4hjh/7CN5AFnZLp5GKqqiGoXPhdfEHn34p2nFn\nceThNTTvgM6M4xl/qYvM8GZe+GIXtY2T8QZjhYeEAlmjYdlrxSy/6GvU9slazRgJHQdTXcSPCQkV\npxplwI+kKPkxJByFsL/ZDle+DUUzTJweTOO5Q2HagpKZOSoj95h4NAX3QTGDuxhGnQHzf2BkXvTA\nm9qB1IuR203smRtJVg4DMFZtk0wq486UvNcVJGuTlYYTE8NmE+12znW5eL7bAwL8RRqrnzpCwe4w\nI/6Rx/i3svjBvU7smSfg0/28F6ynPiKYpOQya+aJiPY7oLsBDYGKpJk0LuUbmNJ0vp27km9veJVn\n5vyEUBKhJx1Du+ARb3vCdpA8pI1gtlpDXvp0HLYy7NbipO7rYrOZb2Zmcm97e6+YkZRgchgpwsl+\nDKqQ2NIMj5Fi1tGCSsJ+itBxWUOYldjDMMHZzDZvftJrXqm20+S1ctiWZYwjAh37XARaLSgZ3XSN\nTU4s1NFpC1vjUlnt6uC6BiXWLqxCEkwSdspUFCalyDoZKlpTGH79oaPg181Y+qjCCgHjna2saBs9\nwJHxkMAPmpvJVRV8SYwEHajXNDYHAswc5j18LAwbEP8N2PBW8u0SeP5v0FgD3Z0weopR0bJ/CfCc\nAuPf4QPw+hOGeuSsxZAWjQ03DiA6090Bq55NfnoJbZ4yMl2H47IkVCUS023IyIGp8w0jpKg87vhg\nNzyyNJ0j65aimI3xvPM7WHz7TCpvht3XgVAlUhMoJkMc8Oy/GBPlVe9B0w7orIHGbbDqptRD+NgQ\nUP3WJy/KVX4iuMtg6z8G3zfsg72vQNEMyLIqXD029tJ+7iZSSvvpYfC1GUbU3ldg1tdi0tqFM6H2\nAwY0Yua+aKN6joeQAlqS/bJtgr+eaqfiYoUna9po0uI7oQKTrVZGmM3clptL03IT647vYFnVCq77\n91Pke1oJaXY2FF/A1gdvYO6NNhyKnVPtfXU6XMizf4vvwEsEW7bQpkZYYR/DcaYDfMv8NhesfwdV\n0ziv8SOeLpiL3kc7XAHc0eqKye01QQsu6rUAwfZ3mVx2w4Cx72szM5litfJMVxf7wmG6IjptusCa\nGSLYbiU+N1hwyljJjSOz+GVwL1ljQmzfWJjQpi4V5lbEh2hKbN0c765lTVcpRgUOiY5CpbmNez98\nkEyfl4/c5dw85iJ2HCwh0GrwJbKcKQz+KNJMQdr6pHY3hZwUWDxJdd56YFF0Tso8yGttI1EQ6Bj3\nVQK35ebG8R8iMoKCgtJPvz0iI3jxYcOGVcSnQpabTOwZgkCTRWg4+4VbpASv9vEUZ5u1HiWJ5Ogc\nomEzjEQMGxD/DZApHnAB+Lth9fPGL+yjVUZ65O2PGiTFHuiaIdi0+tkYB8Jkhq/+1Cj97Rwk+N3d\nkeLnJ6JSQykgBNz372ip8US8czvUbzAoW3o41sqbt8K0x3SOnK9jXq9g9UoyxsMldwtGzIztlzfR\n+PfmrQN3H4zJdMmvoGU3bH5o8P0Bo6zIJzEeFEOC+oo3jI9zb4DHl4JvgAKJUofqt4HomCJBwwNi\nz45W3ByAcxrqgn2vGf/euAmuWQ85Y2HhrfD46QN3NatB5eW5Lh5oDrLqSASzolHm8FMRgDGv5WJf\nb+KD+wSey+H3FxdwbVM97brea88UmEzcmWcUeTMLQeUtWSzLfZUzpt1nhL8EWEx+5o5+nIaPaojI\nP/C3jg5e6O7GJyVzbTauyczE1r6StWoT/vwyxtDMiRziRA7h6PRiioY3bjz0GvXWDN7OGh/rv4zw\nJ9HNlrCMpiYmeyolTkKYZYh3WtdzUt7AMp7HOxy87/ezwucz0jntkD3Bg78lhKfORsSvYrLpuIr9\nbMsO8UpHGtdmF/PkmIN0d1ipPpCFEBKkQUacNyaA4taQMl7OfV7GYUY72tjjy0YJK8xv3c6Fu9bg\njNZkqPQ28b2dr/Al3zd7x9XQmfo3KyW0hR30GDcCyZbufAqzPQnn7o8JrkbcJh+bPQV0hO1Msrj5\nakYBo8xmXvV42BVuIWI6QI6tHrNQGSNGMVOZiorKZn072+UuIkQI6SZ2d41ji9dYpJzqdJKmDC1i\nPjOtHlOSkNqm7kSjLFV6aDxihl5/9Bi+w/h4GDYg/htQNBL2b0/9fY+BIYGuNkOu+sbfx75f8aRh\nPECM6xAJw/23GLUtcgfJPCiuQFZtRvTT1pfAgcb55LofTzxGUWHaCSmNB6+M8ProajqbmpFODevb\n6WT8tAzrGjftpToPvKQbv+65xtgUBaofhfumqFjM8S+C7rqBuy9UuGEfZJTDW/878L7HEpkj4cKn\nY5+LZsC3DsCmhw2jJ1lVTKGCPdMwHFb9CDY8YHglbJmQP5Uhh0NCHnhoPny/GUadBhc+A69/G7pT\nOJsyR0KRT+WB+SZqG57BGziEtzaTVVd8BW+nikcTtChw6C2Y8JqVlffaWKVr1DkcVFosnOhwxK1Q\n0/LDLB57vzGmvmmOQqeIt7luzZu8U1Deu/1Vr5cVXi8uRtLJBABUdL7ADi5mM0qfVaJdD3Pfrkeo\nchSww1VMdtjDvI69mKVOicnOXXN+RFio9J0wFHQmU08aISIIDvmOpLx2Ukq2t+ts8gZ5OGzcpL4m\nvD0nhD2n3woZeLq7m2syy7jTlM2G41vYO9bLu4esrPUFsWeHOGzXOdQ8nhKLh3PztmNRDPNbReV4\naz7XWSfgXv5dCBkk0WpbNrdXnsOajNEEOsywIzaeVo+T7YfzmVDUSN95WZdQ5cumWzO8JJOdjczL\nqMWlhpFyaHVnS2zdlNi6o/dAIRA5g5NrDIPRSO8sJ9ecywV5O9ml7qFVayOfXLZGy4KHNIUH66fi\n0830WLyPdXUNSrizCMHlbjfnZph5T9YT7mMabPfmsaGfAaECpzudvOL1DiHFM/moL3O7yR2uvvmx\nMXzl/htw/tfgzusTtydbTuga+rq3uK8yRP5MC/O+D8UrnyTpzCMUePN5mDfI8vSsK2HfVvSw7K0Y\nqOkq3mAWGzuvY8a8EOYPnjHak7phPNidcNl3kzYXljp3atvouNzX+wQGF3bSuGo7+YsnU5ueGI/U\ndairhxWPStSNgrqPjNMVzoCsMeBJle4uYMxZhvEQCcDa3w081GOJLzwI9qz4bWYnTL3cuEwrvkPC\nLZEaTL0SXvgy7Hw6ZhsG2o1wilAZcslyf6vhzSg/ESacbxz/0f3Jj2/bBw+dAMtWfgBF1QDsuHsR\n4U4bUouKPEf7snM5zFh+OWfzBsydi/zDvXSMM9Pa+SHhSCdWcy4Lvj0S++qupP2SQOGhXdDHgABD\ngrmLGCNeQ+F5JpONl6Vpu9GFQOkTyx7ra2CsryFuUsyI+PnFnqe5aczF0boeBkXRjMapVAFGuGO/\nbuNr9fXcnJPDCHPMNV7drfPtqoOMr6iiJK+Lq3QzWz15bOwuRB9kCpTA1kCA01wuThXFjEsPc39W\nLc7oM9AzHR4JuWjqOpHvZrtxiT7aCr62XuOhw2TnssnX0mkywhAma+JNe2LNdC6YvZVpI46gCMN4\n2OXN4Y12Iyw0wdnCqdkHetcM4ii4OD0ISZ3rG5rw6mp0jMaVbgk7WNlWybLcKhpp7k25BHitbRQ+\nPVHJcbBJ/vXSUvJNJiCbEnk+h2UdYSIUiDzyTIJVNPUKPkWAMRYLN+fkYBOCZzxDqX0jyVdVGjWd\nXFXly+npXNGnYNswjh7DBsR/A2YsBFdRbKmdKhUzCkXodFVHaK+xsOs5+PHFLagpmN60N0HFBCgf\nHy1o1edFpagwfibMXoz4yUPw2O9gzyZ0qVATWEzjtO9z5cPpmLNuhdlz4K0XDM7ExNmw9FKDd5EE\nG2QLh/HFP30mICLp+Ek1vn+MS9rVik0KG5+Of4nXfZjyMhhDMMFJ0eKhXXWGwNJ/AqPOgBEL47ft\nfQ3e+IFRplyokFZseAR6+IB6xAhzZI+FHU+maPgomfStVYYBAVD30cDGhxaSfPS7TGb/xnhW6laO\nR2qJaX0KYao4h0regI8+ounZn7Dyogt5qWE6LSEX41yNXDxjDXJ18u4KoMOR6IKXSQco+RcTONW0\nl6ayXAqqm3oNhqicRcIRZ7RsI6Ka+NGoC3rbDKFyF4v5Gh9wAod4m0q6/H4uq6vjpdJSMlWViC75\nRtU+lk01GLOKAKuisTCjhkKLh5dbxyQ5WzzS1dj1+pfHg0LfqJOkzNpJltnPtrANB/1+H1aXIdOq\nhXgufxbtZicyyjEw2XUsGSFCHebePgQjJp5YO53X9o6hfHILnREbft3ce67j02sNPbA+XT7aTIyG\noItuPfEZkAj2+zPxaSacqobeQ1WVcMA/kBCbJMvkp9TWSa7ZhxBQE0hnry8rLsQRJkSrbKdeNnKI\nGiY4KlhRVsprHi8dmsY0m42FDgcmIbg1N5fdoRDbBij2Fh09L5SUYFfUj6VnMYxEDBsQ/w0QAm68\nG848AcozwKJCZwDKMhJ21XWFurbJhLUogUrAkdYJlGSsR/QnC0kJIycY7X//9/DL6wxxpx6UjzPS\nQQHGTkPc/ggE/SiqiZEmMzGpHQHzlhr/hoA9sitK0upn1JgguLAL00MQUXta1rESwFVjJ29fkhXg\nICuqtCKDJwHQfpCjyoj4uKg4BS56Lv5lfXA1PHFm7LPUwFMPrkKY8EUj+2LC+VA0C7anMh4AGTH4\nEP4hKvtmj4397S6FI+tTGxFSEzStLR+0zYhiojq9AtohnO3g3tO/zn3bF6Gio6GwtauIFxoms7Hy\nA/IP1qD0qXeiC4HH6uDtsbOGNgAETRir9EMlxexzFJB3oJncYCeoFjK0rijdr884gAeKT6JvHq5E\nASn5a3geVb84GXWpjjY3SJuuc/7hw5yblkahx868cYYbvods2HMPxzjbKOz2UJ9Ct0EAearK7D6a\nAp2a1vuoudQg5+fuIsfi73UcLtdqOU09CYA6WY9JmCgbdzK2Ha+xw1WS8KhmjfHQVuUi1Blb3Zdl\nt6NUhmkMueKyLqxCI8M0sObCUNClDVQTQuDTzDjUWKghKNUBPDUSm4jwP0VbjE/RkMoUVxMNQSe3\ntzj4WmYumaYAL2srCBHqlbQ6rB9hjBjF/6TPSSC/qkLweHExD7S381BnJ4EUKekZiiRNUYeFo44h\nhg2I/xaMnwDf/RnccINBCFAU4y1Ukt7rm9R0I+777619QgcS3tx4DZef+BFxs6eiGpoLJy4zPucU\nwp3PwmuPwb5tUDraCF1Y+4msWFOkO0kJ+/dDOAxjx8IAhClbL7c7EZaIytR0wabuCOeLf3A+j5JO\nB92Fmawou4kdNWcmPS4V1OiCrPYDeOL0lKc9ZlDMcOlriYkwb/00GuHpM3n3GBH5k2HGV2LbnXmD\nnCO51k8ChAoj+kiIzLoWdi0f6AiJ1e3rDY2VnLKDmlemJHghFF3w1pTTaIos57yiv/JAjUFG1KIT\nh45CSDdx7cQf8bjnJtIaO9BUBUXXCZnNfOuyHxLo/1wZPSb+BhmfC+jGZiliVOHVPGrycW9mF41q\niPNbNnHDrn8mtLLfnke1PSdhO0KgWcDb4cTsiWUxNGoaf+nowEYr19mSK2HqEspsnSkNCKcQ3JOf\nj9pnchprsfSaNmdm7yUrqhbbs4sXHy9rrxPqU85cmWJmvn0R2a0ehJRxDg/FLMmZ1IUjEGG+/TDZ\nLh/FmV0cCbp4tmk8IaliQhABshQLqlTRUmhJDAZdQnvERmc4NcHQLDTSTUEUFArJ5wgNWISGSWhE\nkghSqegszozlWgsRG16exUtNYA9fPBzklpJqQiJET52Onidij9zHGCrJI/HeqkLwjawsrsrI4Mza\naho1nXhvkeD6zOxh4+EYY9iA+G/C9dfDKafAE09AZyfMnwc2P7z1POGmDvbsn8F7u66moWNC3GEH\nm47Dd/nvcL5+FzRHyWNjphqCUj2pnB0t8MOLYqqTa1bAq4/Cj/8MFRMH7teaNXD11bDTWL1RVgZ/\n/COcfXbS3Y9TclmhJZLYBDCffPb+Q+HrS+/mDOfjva+ANEs708tfOCoDQqgwPip3sfqWIZXe+MQ4\n6efJJ/i6dclX/ooJDq+NNyBGLIL0MiPk0v8YoQ5N10EKCZrg1u95Oe0OwQl2OxUnC5b8ClbdTEpD\navLid7A0d1P48maKtff5m+kJfHomUqr0lPduKdXpypN8yFlUFeehJxNNQuFdfSJP3PJVRu3bQ3Z1\nE10Zafx0xEU02rL77d2XxSASti8TeyjJW8aucJDfe5ppP2zH3+5mp1hAvaJxk/4vMogZBJoYmKvQ\nPjnEkSU+gh1mIj4V1apjywoRVJLTinpgQWGCxcL+cJigNFbG5WYzF6Slcb7bnTLLIMPk7yUlxo9a\nxhkPYPBA3h3t5tTCmTzeltxSLC3swu8y0yaclJLBTGuQRSU+qn0ltGoKlWYzpzidbJat7JRVpC78\nPTCyzQGyM+oZ5ejg5ZYxcWmhALPddZgVnROVBRSIPFZqb9Ii2phw8oHKAAAgAElEQVTuauCj7iL6\n3st8Szfn5e6O81b0hSJgvLOJDzpLaeJIUnEtgaBaryVPTWIcRmFXFB4rLuXHTU2si2axOIXgusxM\nLnYP8x2ONT5TA0IIcQgo67NJAjdLKe/8bHr0X4CxY+F/+6USnH0loSZ4rsTQA+gLoUDeZHCedTKc\ncRK0HDFEnTL6/Ag7W+Ebp0GkXwzR02mENe5fFa8Y2RcHD8KSJdBXora2FpYtg/ffh+OOSzikTLi4\nQBnBcr06GsMWaEhG4qLy+RIaTK0stT+ZMC2V5WzGYvISigxeGlAoxiQ873vG50Nv86l7H2ZfHztf\nf9izDG9DMjhzY383boOqlwzi57Z/GuTJvhgqgbKnBoXpHgffO6eWsyfYuSUnhxNuEky+FF6+Gvav\nAKHoCHR03cS4mR+xcMpylD/tRYR1hFPytdMuYPneH7G98RQ0s6SlXKel1FgZS1SqzNOidy85PBYb\n1XPGUT1nHAFdpeVwYnw8y+SnPWIzwgzxo0BBkpt5Eropm58daODIlnT0iBGa0FF4gCWsVibypv5z\nHITQFZXyijnkqmo0/79fixHoztdo3pROxG+ix0hRzDrZE7rY78+kwt6eoJcggJsyJjPSlI5P1zkS\niZCjqmSo8ZO8R9d51+cjKCWt0fO7BpGQTugjAi3Ny61KEXe0tPS68SWCHIefDGeQiFDpRuVd4EJl\nHAuUEhb0mx9nyql0aJ3UEXvwVFTawibSTEEjwNNvnD0GVN/N2WY/XyrYxt/qphOQFqwiwmx3HXPc\nRyijmHLFeIWfrS6lgSaUjLfp1izs9hkPtoLOebm7sSsDJ1xaFD2qEimTmKS9PRz44gFFJhMPFxXR\nEInQqWmUm81Yh5hCOoyjw2ftgZDALcBfiT2ziab6MAaFMw9Ouxteu95Y1eoRY7VqshniS4ARVsgr\nSTz4Z19JNB560NUOV8wxiJxf/qER6uiL++5DhkLx/AopQVWRv/oV1Zffz+7V2UjVwpizDH6AEHC6\nUsIUkcWHejMBNMaKdKaJLLZKQWHmrqTlu82mAKdOvYt/bfjpgNcibzKMPx/mftNIf1z1IwangB8D\njD/PINErKmx/Cpq2gbsEplwGM66Bd+9IlPTQNZh6hXHJVnwHPvy9cd/AMBaEyeA9fBIUrnbwZGkX\np7tczLLbSS+By16Hhi2w86FGtP3rGD1lMyPG7URUNUModu1dtlZyJq9h1+QF6CQake5mK5JEUSOB\nTmlagExn7LmqDaT3hjn6IsvspyNiS0Xz5X/bunmwy8+OGnOv8QCQhp8z2Ey67uNPFaczcWQz7Rlu\nXJZMfhjI5MamlhiJMVpTeuLvM1k3TRLx9/TDaEsPC1p3pbHKPZL8Ai8uNdRbQ0EVoIYmMtJpzNAO\nRYmrGtmDVzweftLc3BuD73mhBXV1UP2F/qP24eNit5uTHA6e6upiU8BHIL0OuzXS23KvZLNew0JR\ngEPEv85NwsQJnMgOXzPS2orNpLPBY2dHuJZ5Gclzn3v42T197aETWBWda4s34tPNONUwqjC8UVki\nlmYU0YKkN9cwIexB5OxiXvphGkIusky+lJ6HHugSqgPpgKA2kM4Ie2KOs0RSqiR5f6VAgclEwXCK\n5qeKz8PV9UgpB5DWGcZQMecbRlrjxr9AZ63x9+yvGymMKVGzJ544mQxaBD5abRS/uvImOP3S3q8C\nb23ClmSlJyMaL/7rXLa8WIgiIiA01v1BZfx5cMFThpFTLBycp0Y1lwM+ePcZJnVsxVSeWq1uZuWz\nfFD1Zdo8qQdVMNWQczbbYcNf4L1fDjy8YwIBj5xkkOgVk6HdoJgNI2D1rfDF5VB5miHypJhihsSZ\nD0DOONj5rGE8QD+exCc0Hnr6pgIrvF5m9ZHsLZgKBXfnwUurwdNkzEjtifLUZ7GcpbzACs7hj/yY\nvutTdyDEiWMO8NaeyigtVkERRlDjhuOaojQGSbbPQ1lXE8exn+0U8BrjaMdwiZfbOtjn7x/WMBIw\nCyzd1Ifc1EciWNIE3ui5T2YbD/MXXATRESgHJNXBfN6aP4tW2pnnaOCRojIe7uhgQ20I6x4Tox5J\nJ2OdnZXHJVujCPSQSkuri7/LqUx0NVNo6Saim7nUMZFZzuQZRT3YGwrxw6amhGqTABW2dnZ6c5jg\nbIkzInopDv29ANA7MeeZTHwzK4sqqXKnlvxhiCDZK7uY2mcy16XkV1uC/GlXEF/EhqCIKSPqOG3m\nVo53DKxiKQQ0BJ2821FGTTAdFck4RwsLMmviqnkqKIxVRhGREfbWLmfkmldwhELMAWaoCuunTmDn\n2IrUJ+rtK2hSYU1nCQJJW9iW1ICoFOXkk5vYwDA+M3weDIgfCiF+AtQATwB3SzlUR+0w+qP0eOPf\nkNGYvPphUkgJf/+VkZ45ewmBTqjaMoJJmFD76cHt4AK2aFcCoEtT79t013Ow6SGYfhVseQS2Pgbm\nQAPnjrwSW+QIZiGYVCZ7Gdp9Xcm6rtDmKaPNM2LAbm59DA68AVeshjV38x/JvOhpXwvF1Ct7wkla\nAJ67FL5zGOrXG2JMljSYeKHhoQDY9ODRaTyAoSkR9hreJ2ECTwptpCMnGRNGKBk7XVHh5B/Du/dC\ny16wmJBACAtmwijRgalEOJNnseHnN/y8d9D5sxqYO20npbkdrNk7gg6/jbLsDhaP248zU8MnJRWt\njeT6PL1Mh5G0cRL7+DGn00gaKjpl1g5qgj0+eEM9URU6BRYv9SE3GmDLCoOQ5MhuHuV+LNFnrqeP\npXWNTN9WxfppE6jR6zjVNoYZBQU0NMKD1xj3pbFk4AushxRC0sSm7kI2Uchih4NZmQMbDwDLu7qS\na19KaA47Wd9dhE83M83VgFmRaFJwyJ9OhT1e5VUgsGBmrKiMa8c8iAZF/+9/vTXIb7YFex97iSDX\n5SPX4kvpCel5PJpDDp5snBTltgg0BDt9uRwOurmicAsWRceBnUXqfJzCwZq2F5n7zgsG6TMKk6Zz\n3MbtdDsd1Jakvn5SwkF/Bu93ltASdlJg6WaiK7aedOIgjTRGKxWMEiOHSZCfM3zWBsTvgY1AGzAP\n+BVQANz4WXbq/xQKRw6+Tz/I5/9Gnb6ED+6ErvBXmUqiNvRWLkcQQfZ/xIRk898F+16H3c8bXIXz\n596JJdRg1G6IktN6Jn0pDQNEERH8oXSeWfNbhiKG4GmCvy8CfxufvvEwCKRucBn2r4Dx5ybqQwB4\nm4/CeBBgTTMMEqmD2Rnh8IdhHjvFRjgEQhPoqkTRBDtuaMdXYky0Jzgcydtz5cHpd6C3HubdB1Yw\nveQh3MQLZvRc8cW8zh/4MUEcgKB0Xg0IwbSyeqaVxZM8GiMWiiIBcn2euDbUqKT0xWzivu6F1D8z\nkcWdHew+uZs9lWZCUqXM1sn0tHpeaonloQoBiqJzofYh5iTBEAUYt/cQ66eOj5toCqbCNevgnZ+D\n+o6CKQyRFJQesyveED4vLY0nOjvZGAjgFIKL3G4mJCn/3BCJJI2SCWGUydZQeaejnA86S0lTQ3g1\nM2GpcErGEY53t+HByP7II4d56lxsIv4c5bjIwkI7oYTH2YWJMSJWxdYXkfxxZzBhv2llR1IaOT04\n4M9ghzcXnZhoFNG/OzUrB70jOM9tZbqYjEVY6JCdpO1ba4y1X7s6MGn3fmpLCuLFrPqgM2Jlvz+L\nXHOA2e4GxjhaUUVPCEhQKoqZp85J0uthfB5wzA0IIcQvgYFKG0lgvJRyj5Tynj7btwshwsADQoib\npZQDVl35zne+Q3o/FbFLLrmESy655ON2/f8mSipg0lzYPogiUx9o+/bz4HFE3xhzeZm/cDrXYyLm\n3gw6cpC+JI+XFNRvMlblAApBxhe/gaKknuW3HjqDmpZZ7Kg9LaZvMRj0gWtOHBMcpWejPyGyL8rm\nQ8Om5FkXJiuE/dHQh2Zsy6yAu0slthwvIy95n8orPuS0V0vY8dhZbP4wHV9+hP2XdFG/2I8AZtps\nLE5lQEQRtpSgdHvYImezQKxKuo+Czmh2sh1Dx6FhWxFFsxLZoT2SyiXB1l7Bp75QkczVa6mdX4bq\nVfGLYkb8UlBR6iXvjTeoz1FY2VaJR+tJIzQEiIRbobC9Aw0FNUlhEEskgqrrlJvL4rbnTYIL/gkg\nYLOV32zrr5EgsWaEMTtjbV7mdnN7czNNffg9yz0e5ttsWIUAIbg8PZ05djujzWbeSHK9pISwVHtn\n14hUaY8YYSSBJBwu4UJ1AQe1Tjb5/QTVLo5YW7AqFhwiFm5ShOArymju0XeiIfuIaAmuUkZj6pN5\nUuvV8SWJdqiKTOl96NIsvNA8jtawA5PQkxBaDewJmtghd7Nb7kXqEhtW5nm8cd6H3j4D6d1R4zGF\n9l2GOcip2QeSdwqD9DmMj49//vOf/POf8anOnZ1JNPQ/Jj4ND8RvgIcH2SfVE/MhRp/Kgb0DNXD3\n3XczY8aMo+7cMJLgO7+FP/wQNr836K4S6OguiH0ANnINa3PPJb3iVTL0Vr5a8GdG7t9E7a45yIR8\ncIkWiL3FVCWc0njoedmNLnyX1zb/ON54UMBkMeSpjyVchYnZEr2hhf4Gw1F6Nkrnp/7uuG8boZ2w\nL2ZECNXgcXxlDdSugcatRv2MrY9B4zajSmmw08nmn59K+648Zt/5ErN+dD/TMs7imUgpe/whRipm\nznG5uDw9HdMg7l+LCyZXrOAJcTELSG5AALT1ycM/9E45FYsPkFXebqQLCoEuwatZ+KiriAq9iTE0\nJm1HRAQmb1RLsicEVOtgz5lLee3VOmJzh/HlosxqSk/pQt0Alv1JeDdAl8tJgVJMpShP2f+bp1qx\nKvCHnUG6wqAqOrNH1jJnYjWHAkWMVYu5xJ3F3a2tccZDD94PxB661T4fY81mTnOmzgwKdJixZoR7\nH2gVHacawqebOcWeyT3tLawJH2BJ5n7MiuRDCR9GBNPVSUwTk3u9KeOUDO4QM3hbb6QBP7lYWaQU\nkC/itVnybAJVJFZV3X64gBPH7U8q0fJRVzEtYWMMYakQn1prQCCxRnUltKjx5sNPl8uJFCLBiNAF\ndKTHdDOONvogkVQoA4crhzEwki2qN27cyMyZM49J+8fcgJBStgJD1MlLwHQMz9cQMt2HcczgSoeb\n7zf4EI2H4W93GCXCk0AAa/delrBdbcvm7RO+hG6GaVQxfdQzbDhwId5gJlIaj5kQGlLGv71CERcd\nnkIyXClyHAGnrZ25ox7lvd3XxvohYNx5sP2fHLMQhTDB1esMouOqm2Nqj8VzDDLqqh9BV5QyYnbC\nkl/AjqcNOW19ILKjgCmXGpUxUyGj3ChRvuK7cDA6d5cvglN/Z6ye8yYZK7h7RkXFdbQ+ugkSqp+d\nzpivrCF9bDPWrje5fcR3EYPoISR0U4AjU2O/bxztZOGmA7WPYz6Cyn7GcoTy2EGaSuQ2M9PLn+HA\nxcejm02UvbSBNf4ySuY4yd29CWVZoudDaoK6leNI9E0I0vZZmfaLLHZd10Ewxzh/pa2dCnsHAMpM\nC8HGTKzezl42as90559yJqeYFieUme4LRQhunGLj4gkenvK8i9MaxGI2JsRyZzdOaskRp7Pan0go\nTYaqcJi6FKs6RUCZYuFISEO16JyQUcP0tAYjZVEKWpC4gNP6Hygkm/RtpCvpVIjYJJojbJyvDjyp\nZloVlo0w8UJ1JM6IeKeqnBnldaTbA70eAQk0hx3s8RkETAWdHLOPpnCiQSRRmOBMdOvtHl3O+D0H\nEzxNioTt4yoT9h8IPbV9JZIpYgK5IrXmwzA+ewg5QE2FT/XEQhwHzAXexEjdnAf8DnhFSnnVAMfN\nADZs2LBh2APxaaGlHu66AQ7tjtsshWDt7stZueVGkvEQGit0Ds7SSdfbuEP5BrneDlZv/ya7Dp+C\nLhVUJUQokqjkN7H0Vc4/7qYByV317eN48K1nkLrBmzjnYfC1Ji9I9Ukw+kw473Fj5d+6xyA7ZkTf\n17pmSEGHfVA821ixd9bCY6caZcJ7aok5csDsgM4a4+/Z18OCH8VUMQdDtJ4Sln7v8D9u66B1SqJ8\nOQBCZ+qPVzL6f4xQ1Oiyb2MxHYVwjq7DyifhqT+i+XzUUUoeDVgJoGHCRIR6ivkp91ArRiGlkRXs\nVrzc89I08j2HkjYbURTq71pG17IpSF0iFIOYF2y3sfq8q/HWZCU9TlckDQt9vPdgIyCZIo9wW+PL\nBC1m9o8sZbZ1PqXrXoG6TcYBtgyY9kUYvWTIQ14ZeZM66pMKLc0Qs7i0eog3bACowLlpaXwjM5Nn\ng2uwWGqGvBKXElzCyRilgkKRTz55+NA4FPbT1Gmi2GJhTHpyF39LKMSvq7eQl3sYk6Kxoy6fdQdK\nuXjuZvLTvQSliidiYbcvh43dheSZPSzJOkiaGsKk6LzQNI7qYAZK9OpIBMe5DzM/Iznpuri+iQVr\nN+EIGKGhsEll3bSJVI0uH9JY88mlUpTTQBNmzFQqIykQg0iyDuNjoY8HYqaUcuMnaeuzNCCmA/cB\nYwErcBB4BCMLIyX/YdiA+A9BSji4CxqqwdNlVNecMIs/n1JA45ZEPQOAhT+B/e06q7bo+F2SGcEN\nzKg9QHd3Efsa5qPL1C/kyxZeQ2XB2oTtui4IRRyIghI+yF2OLRMmXWTUuPC3w72VEOhkSDoPqiVK\nyhyQXQNFc+CaoVNCkDrs/7dhRGRVwqilBl9BCxv/f2Li+NY1NK18iv2Huln5pweT7yMkM+74FxUX\nbwQE48pvQlVSyxAn4OFfwutP9H7UoyJOb3AmzRRwgLFok05gwWIHb74n8fpg6iTB2bfNJ3P3wBdL\nCkHnsil0nDsVbcYknAXTeGz6XLy17uT7Ryf0N5+sp2V2AEXqXH34La6vfcPIC5ASOftKlHFnQLAb\nQj5w5gxd4zuKRyNPEybxYRAIKsQIfnq4hKYkKcqpkIwSI4Abs7K4KN3Gk9pzH0sV0hBag0ZKOCBN\nICS6Doer09EPlPLX411UuGNjj8gI/9JW0k5H7HxSYBYmZovpPO6p4bnWRPK0Ww3wlfz9jDCn4ZQu\nOoMjWOVvpw2D3JhnGST9U9fJa21H0XSaczKJHKUGgx0bDuyMVioZJ0YP6EUaxsfH/xcGxMfFsAHx\n2aLqJXjynPhtisko1PT1HcZqvGZwKgUgyWI3bYzDeM3qfHnxlYzI3dwrZKPrgohuxWIKwoXXwQXX\nJbTSsBme/RK07DoGg+uDLzxopJp+5njuL/DUH9AUBVXX+ftbf6OmeWZvWAiMCVcx6Zz1we+wZvtx\nOydQmh/V8A75oHotdNRARhlUnphYp6T5CFy/lGSuHB9O/jTiIY77QiXz5llQ+0s05uRAa2LEMjGC\nDlJVEMvOheXLefIc41lKhrBd48N7mjlysg8R0XHvsnDFpo2MMDWwsGgtTrPfaP20nxqGgyM7uZUW\n9sP+t6F5D1gc4C4yXEphLzRXcUjWsb80l5riQmSfcQkE48UYuvzj+E7T0KKpFqC/FJsCOIRgRVkZ\nPtHM63pqXkky9BV02ks2TdIVN05dh8YjaVRvKGfDsjRsqvFdlb6P9/VEo04gGCtG0ay38ky7m02e\nQnruuQBOyjzE+W47i9R5vceEZJh/aSvo4NgR74aCEZRykrpgOG3zU8CxNCA+6zTOYfyXYewX4Pwn\nYdUPoeOQ4bYffQac8SfD7W/LHKqegeBUvkc1S1jD9wCFv7/5DyaWrmDayBdwWDpo7S5j0ogVUFgG\nS7+UtJWCaYbh0rTdIBg+d6kROvikePuOz4EB0VQHT/0RADVK5jt75u08tPoRfMEMdMXQHBY6zPz5\nK1izfdgsBRTmnGEcf2QzrPo1ce6ZtX+GmZfDhLNi23auJ1UcyIGX739dgfIU3owFC+Dll6HfSj3Z\na19oOlpDLSpw4s9g70qJFgB3Ziulo/YSCNjZ3jCel1YcQUmXKF0KJX/JhVY7/xJ5aFLlr7su5Wez\n72JSdhWsuM1oOL0YZl8FhZNiJ/O2woqfgLcFELQ6nKwrG8PM2n3kebuQwAgE5dXVHCou4M0TZiGj\nhpVEMkoZSY7LxXciEX7f1jaog+va9HSsqsqf2tvxRxdlZWYzd+XlkaGqSJmiCN0QEEI1KpL2m0wV\nBQpLutm2OcDLNTYuHGmoY9bJ5HwiiaRGHmaaOpmTstYxLa2BQ4EMVHRGOdpxqmFGi/gQkEWYOUs9\nlZ1yD1X6XrxJVEc/DVRTS4NsolDk/0fON4yPh2EDYhhHjUkXGSJIngaDTGjrE2qfeiXseXlo7Thp\n5jjujhoQAAo7ak9nf9tJzJ7yLxbNfxpx/HWG8eBKjOdHArD7eZ3O3W3kjvIw6oI8iuc6jokB0XnQ\n4DwcpVf82GLDWwl+8ey0aq5fejabDi3jkaKv4ClUKL+0jTnTM7BZv4TLPspYtQU9icZDb7uPGt6I\noinGZ9sgqbEDfX/rrfDq/2PvvOOjqNb//z4zu5veGyQhQCD03nu3ICB2AcvFe21fC4r6s3ut2Nu1\noldF8Qo2EBUQVJr03ntoIRBSSO/ZmfP7YzZ1SzYUBZy3r7zMTjlzZsnueeYpn2e+IzbkSGh0ZOg5\neyAEhV0bEYKhzeD38S7+WfgOYQG5VWtjtgxgx4472BqXQNJSf5Rso6Ol5vC4lNptPLfhAb4ccQ8+\nqiP8kHccFr8II1+E8GbV91icDcCqZq2Z1nsEF+3ZTGSRoW9RUwy62bETJB45zsHmTZBIeipdiRSG\nMuatoaFcExTEr0VF5GoaCwoL2VtRO+wxzN+fOyOM468LDmZPWRn+ikIbm63qCTpMhBBJBCfJdhnG\nqCt1XfN1MVZcm2QGYaGl7Mur/ndWURxSXM7XUVFpJVqQLjLAepgIa7rjnZB0VToSqziLPtmEjS6i\nA9kyhyJ5Bj5cXiAQHJXHaIxpQJzLmAaEySkhFCMPoS5tr4Lud8DGj2p6ImrnZwvshHKEODYikI5m\nTMZKffMSaDbYByGuBq52e/0TW+DLi+wUZ1kQShhSjyTy0WNc8coyds+6FKmfpuuzuuWCQfpu5N5f\nKck/Sk5YYwrbXkJSWHuUs+lidVFCCODnk0+/1tN57PHh5AeH8XxcPFG2OpLBh1fhMTFkzUdw1fvG\n7136g2+AISdec9FRFGjaGholuBwCgG7dYOlSeOQRWL4crFZKBrXDd8UOqNARuqNqRBXo/jZO3tCF\nEIC8Y0xiCtZArdbbHCaK+I536XX8BXz2Rjp1+pSoFFQEsi69KwNj11VtRUrYNRcG3GOUxKSsBamT\n7R/ItN4j0IWgV8o+10JKCDqn5BHS4jKai6aEiNq5GaGqynXBxrbbw8I4UF7Ot3l5KEJwc0gIja3V\nuT0BikJ3P9fehqHqABZqi8in0GmfIhwLviP2U/PPygc3JT52sK0NImB1IPGjqz9fzUQCB+Rhp8MF\nghaiGYpQGKz2p51sQ6o8hoJCM5HgdN91sXhYLtwZLKeDUo/6pslfj2lAmJxRhIBRH0KXWwylydwj\nsOc7DV2TVb0SrBRzFRMASQ7NqowHWxDE96o/6VC3w8zROiXZjudI3Tg/+0QjFr2Uza0zlvLpTUNr\nJ0sKQ5BJq/BS8VEa5ZlN+kL2ut8I3/sJAP6Af85R9IPr+KHnRQxsfQPRwo/SUoldg8CAM2hQdB0I\n050b02pCsKdxImHhUbwZFUVzF42djMxSDziezgHw8YNJL8Mbk6vVfqQOfoFw1wv1z7NvX/jjDygv\nB1UlN3s+JSvn0WjKLwRsMJ5Yi3o358RTI1GaNGVFcTHvpqXzti2QRuW15ykAXyqYwGqWc62bC0ry\nyutU80gdTiYbv+t6VZbv2qatjGVNCGya3XVoBUmo7ksXpWP99wq0sNl4LKrhPRmCRCBXqWNIlcfJ\nlflUUIGKSoDwp5lIIJ98TsgMVKmyVe6gmBIkEj/shFBCnvSt+nD4Lgwl/F9JWNJtXAocf0my6U3o\ndiskEEeLAl8OBJUail4OaddAEUAC8ehSJ5scBNBZdPA6WdHfQxjmTBsPElnV5dPk3MU0IExcIyV8\n9BH85z+Up57A0rolymOPwtXuvQKVCAHxvY0fgIJnStnY/i3ytVgi2EsXPieALABW8kiVm37o80b5\nY30cWgz5x5y/9HRd5dCujvjnP89DGUNZ/jwkLwDFBu2uhsQRMGO09/LWhemSTz7N5x/qNFBrOyQE\ncOX633jR2gH7rB6s22S8ZYnN4NYbFbp2PIWnp/wcmDcd1i8yYid9L4FLb4AFX1XViEpFRVEUYv71\nOD/Ex7tPMouop4mRWsfo6D4E3p4LS3+ArBPQJAmGjIUgN2WjrnAYMmHB3cnptInD3/wTpbAMBOgB\nRg7FUd8+PHTiBFiCiCnPc+uYH2DfwnK/K6HE1VeUoE1Y3QZwwkimBENhLDIJspIpsvmiINGAbbHN\niSnIRXVKHBcQ29X7+zwNFKGQIOJxtTRGEE6EoyFWgoxjjb6RI/IoEkkvytkhQkijHMs+X6KubAv2\n6nevvEDw821GMnNszCwWF9vZ2rQlSYE5NPfNxUexU0AhP8kF1BTw9MePfkovEurpcnlSy2YbO+u9\nPx9slDmlk54aJ2U2kcJ1ma/JuYFpQJi45pFHWP3VHr7oMJMjnTrgYy/i4imfMzHtU/zv+VeDhgpq\nHcTgTVdScfk4bEd2AWAXvqz2f4It5XcQ0xb6Pwod3aiQS91ovLXxYyjKgMB6ehsVpZURGgoXv2H8\n1GRSMmz90mhelbW1GA0brj4GQpEkl0kytm/H2t3ZZSGAogp/tk5pTXGJRErjy/zQEXjyRZ3XnxW0\nbdUAb0R+Djw+Dk6eqA5dpB6E+BZw1xRY9iPkZCJadYbR/yCySUvP48V2NdqBuqtZbTHEeVt0HFx3\nj/dzdoOfTyyxkWNIy5qPHliZfCmIDB3A40WBSCpAUTniG0nT0iwXUlLQ/8Amgq9MJX9GM2rVdAhJ\nz8ittAw5XOcsCa0uqn7ZbQIsfJaWmcf5pZ0hu72wTVf6HMrEqFsAACAASURBVN5DUFlJbSMiKKZB\n+hF/Bv7Cn2HqQOxSQ0fDJmxIKUmmgN8+VMnUBcg6SpEqrH6tgrUv+bEspg16mUL/8FR8FM2toVlM\nCYv0P7hcXFplvLjiN7nMu3njT1+lJ/v0ZI67USD1lpX6WoJFkJlIeQ5jGhAmzhw7xsqZ+3lhwGyE\nw99fZglgXos7SP5pI6//sxTF37mhkCdEp47YDu2AbdsgNxdL164MDA5moKvLp0l+W6JhTztGQryg\naGE826YpRhqFblR/uMNiLSeypXuhB99Q6H0v9LoHTt74GhtnBLKGydTW0NPp1msbCzd3IE64d1X8\ndnQQRUUBtZsOOZLfZs7WeO7RBny85n9pGA8FpVBqhyAfozYwNRmKC+DfbvQf3KEoMOoV+PlBnNwt\ngTHQ65aGjddAwoK7ERTQlsLi/Ug0Av1aoCmBJOceptIY+CR+MFOSZzmfbPFFvfZp+lYsYe3Ng8n/\nKR491wY2jYChmbTpsh6504i6V9HhSkjoXf06ph1UJNJp+w6at+/FkfBo8v0CeP6ScYzauZ5uqQfw\nryjDltAXek40yjwbSEGF5H/JZSxL0/C3CK5uZmVkE8sZzYuxCJVKTW8hBEkEsy4ZMl2E4aQGJ3ZJ\nlkS0AyDGWkCE1Tut9536Xgaprtv4lsoyir2svsghl+X6avooPTmun54BAbBZ20Zjy0X1H2jyl2Aa\nECZOyD+W83mH5xFSR4rqMgRdsbA7rDeb5ybT/bo2DR9YCOjc2eMhS1fqLHh3HXfLKTThMKyDzPzm\n5EU9xZHMnsb8NFAtZeiatY40tqTvyLn49Bjh1VQid//IRWzFj2zW8AAlRCD8ShDX7iDnsj/I2dmC\n9NQO6LJ2W/FK9ua6lunVddi9r94p1LnxX2DJAUh3yFAqAlqGQ6fGRjXGyBsaOCAQGgcTvoRNXxla\nEKoNOlwBScOcDtUqjF4c2/5nyCS0vBR632fYGqeKRfUjNKhT9TV0zZFqZ7yZc6K7E1ZRzF1HF+Gv\nG27v3LIgnlz+OM2ym3LFuI4cbL+dgBEZaMVWVD8NaZFYxUhEm+shdaPhnorranQUrUu3kSgvz+WB\nI+8w+5ZrWdmqA7n+gfzRoj0ReeV0HvIQ+HpOHHSFrktm/KLx6LFiinwNI0YR8MORCsYnWnm/n99Z\n1S8Ia2lor9SVTxcqqM2N91FFZ2CodxUTEkmOdN/pLVNmNWh+OjrJ+kGGKgNYpa87rZBGutnV4JzG\nNCBMnCi2hZAa7NpAUPUKdmaGcWZasdSmoFDy3Qf7eVvehVoj8zwi6DA3DrqDj377jqx8Y9HW7D4E\nhuZQUhSAVmHDx7+IfqPmMvBRIKl+AwIAqxUFnUG8CP/YzpevPAH+peh+FlLsPfG5YjtFr7Zm6bF+\nDItf5XR6sK2gyitSl5CGrEu6DrNXQ1ZR1aalg4fwzYQJpDeLp7NezE3l5SS6SpasD9VqPGH3nOj+\n8hp8fQUk/1KtWpi+RWfLZ5Lb1kFwzlrISIW4RGjbvXaWa2Ee/PYd7FgD/kEwcDT0HOYyE1YVgsiA\nEjKL/KgsNZgWP4ivG/ehdVEarQ6UsGbuRYDg0ArJgcMBPP9iL/5Q0tgflE8QVgYo0XQUYeAvaocs\nXNF5APQYiv+GJdz44sdMCPRBt1qxVKgwZcYpGQ8A02bqvJ5cRlEzWRVZqfwTmHmwgqubWxkee/oy\n2HUpzYVNn0D6FuPfrC5Sg1aTjUZYYyL3kuCb73yQCwSCIOEsMV+JVTTsXiSQTiYXi6GMV6/mqDzG\nIv2PBo1RcyyTcxfTgDBxwnbJUCxfl2NXnBcsXagENT07DW7WbJDcan8FCxW1kusUIZFCp0/Sl8zd\n+EzV9sLcMB6I64yc8w0B4cWosSMbtihcfz2sX09xkD8z3r0P3bfC6KgF6BYVISXBtx7k9Qf+D39L\nCX0aba4qUhACmg8pQX7unCwpgJHDG5BEuWQJZFZXI0y9524ODenGpfs3U5K/l4UdB3B1aiqfxsbS\nzbdhoSNv2PsTJM8HaoViFIrS7SwdMZfLuz5VtV1LaMuKYe+RaY+kTXQO7addj8jNNDwBigLrfodh\nV8PtT4MQJB+ULFmhU1wKndoJBvfUmVdup6TCWlX4V6JayW8WwqZZXarmoOtwOAX2bLJwVe9T7Mio\nKPDAm7B4Niz/GaW4EKVTPxh9M4THoEud4/IEpZQSKSIIFfX3DsnNk8yeKzk53O7cBwywCPj5SIXX\nBkSJrjOvsJCNJSVoaj7N/FOIshXSWDSik9KOYMfCXngCPu1riKTJyqroGqurxQ+6vFPBHwMLiKso\noIV/rlfXB8MD0VZp5XZ/NJFYULG7aJ/uCYFAEQpNRRMG0pcV+mo4C+WeJn8dpgFh4oQ10JehSUdY\ntD8GXanxJyJ1FFUwuP/Zqc/2P7KRLqx3mZmvKhqNw3dVvRbYacYSgo5tQxPFqImnIGt+553w3Xfs\nivOjws95YZYCLFHlxHYt5dkND9EsKIVR7bfQpZckskNvRobEU47OR18Yz5+G/Db0717GFUMrAC8r\nGHbtorI94vGEOPpbj3Hnt8uwK0ar63FrF/Blv9FMueouZjVpUv94GceMnIodaw0BrsFjYfDlblWx\n9v0EiqKh67X3SyzsOTKYy2sWKKTsI+jzx3lVTEWXIXRgCs8yCX+Kq5M/F8+CgaOZubsb07/VUR0d\nuxcskjQf2ISut+8mq8SH/HIbFkUnwr8ENgeTsy+w1vVVFfbslwzozamjWuCi64yfGmTJk/yuLaOY\n6o6bzUQCg5R+jrwD1+zZb/ShcCczokso96IvC0CGvZzxx1M4Ya/M5xDI/OYMDD1C7+ADHNIOM1q9\nhDARypKnIS+1Rg+aGtcY/jIk3mFnXN5xcos0ugfnuw27uUJF5bCeQqgIwUfYnMo6FaGgYmmQARFH\nYyyi+rsjSUmkkYjmgDxMqV7KYVJqvffuCKMBDeFM/nRMA8LEJbc9nkDyk6UcSgMVOxIFoQoeukcl\nPOzsxHe7Hv7C7T5dV8kvMgLyAjs+5DOS+wBYu16nn4eYypoNOj8v1MnIgqREwVWjFFomCvD3hyVL\n0JfP8Tivpx5S8M9WsVqbExpSuzxy7EiFvj1gxeJ8yrIz6GaZQ6yym9TpYUTGhxMwaCKEei6Ro2nT\nKv2FnH6taXf8IACWGkJSN62ay+J2vUlv3JgYT02Kjh2EJ280RKF0zTBMdm+E7Wvg3pddi2wIHIu/\n88Ip6iSRqmh0Yy1R8hjpxLGLLnzCZCYxBQrKYE8WMquY5N3/Znpbo9mFVmOxO7IyiBFNOuA3Oo29\nMo9ALOyfEU/eLzHUVVuUOgQHnfm/Nbu0s1BbTHmdRlqHZQoBuj+9Vfd/TP7+DmXJdJWsOM3JC6ED\nF8V597X66Mm9pNv9wSGnVsny3Ka08Msm0lrGRm0rIyyD2fkNSBd6UooF8lPhez2fHE1DB8p11YNu\nJQxnMEtYju6wQjQ0dst97JH7kUhCCKaL0pEWSrOqcyoamMfQXenitC1IBNJFdAAFEmUzFmiLsLsT\nyXLQXzkd69HkbGMaECYuCQoUvPuGL2s2SvbssxIcJBgyQBAVcfaSw/wz97vdpygaWQdiaM7vxLOG\nnnxAACfI8ovlh9SO9HNz3szZOtO/0VEUY41MOyFZtkrj2Vsz6ZE9B8qK6diuGxZdYnfxyBaKjSYi\nACXSed/en2DJw8Wk7/XFarHRoutJ5vXtzuL0SWjSglWpYOSqZdz6ZDDWQA+hlZEjIT4e0tJopueg\nukiqsCsql21djhg62sUANZjxdrXxANXCUCvnw4hrwVHSWJM2YyVbpjm73IWw0y7+V5eXiSSDdOLQ\nUfmdMdyZ8yy2xcmgS4SEpcoQVL0CTak9rq7D6p/8+XZs66ptU3WNn5FOdy0EDO1/5v/eDssUt4l9\ne+V+esguqG68EO3bQEQ4lO+3kRNTgmahVjihb4zK6IT6wxeZ+kk2FPnhLPhtmBN7iyKJCE3lKMeQ\nUqJXuH8f9ApYXVJS9f7tK45gaNhhqCOPLRAkEM8BcRBXTRQrQwt55LNMX4kdO62VluhSR29g2KFc\nejY4okUk16hj2KPvJ1keopCiWvtVFIYoA4hWGi7YZfLnYRoQJm5RVUH/XoL+vf6kC0bHI0+eQNSR\ncJZAdl4oA9Kfoo+wYJF27MKCROG97u9TUOL6y/5ktuR/3xljVQ6p6cYX9Psfl/GZmIpQFPx+/pyX\n2nTkiYdvw+5jo2aI+QYl0WVZ3o6vYdZ4ACMhsMLuz571fdE2SZTLNDQ/qNCt/HxoGOWvJ3PfM+3c\n37fVCgsXIi+9FL+KMrC6CBFJSVhpBdGevA+6DpuWuZbAVlVjnwsDotUYQavgJezLH1olKy7QCPLN\nYlC7j5yOt6OSSnVeQgU+lOwqwqbLqoW01BLoNtZdWqey8B/jFJIPauzcC6pihAEUBR66WyHKheF2\nuhRS5FZ62Y5GOeX44Vp1UVUEj9+v8uSL0GmFH2ktKsiJ0rDoMLG9jSf6+WD1InaQJjMdGiTOCCQV\n0vibVhwGRtJo2D3LWUVVt0PSKAhSlKp83mLdxsLsllwSnoyUhlS3gsRP+NJH7cEP2lyv8hA26ltI\nEolum3N5YqfcQyyeBVv8hT/d1M50ozOa1CiWJWi6jq/ig29DWtGb/GWYBoTJucPICYid65w2C2D1\nlVNZWZ7G6H3v06jwIIdCOzGn1b0ciujGmI6uv7A3bZMu11KJ4ISM57C9JU2VAygKhO/dybM/rmPG\ndWPIpIQmIpCLlVgSXWSnSx1+e9gYqa7bXdUESasUdg13NJZC4dfdLbg5VxIW6mFhadcOfdgIxJ7f\n0ZuGOOXnWaROkX9/9+eD8bgp3JSFVO53tVmB66cXs/WKf7KOuykhgsZsZGTHlwj0La11jzqCBVxF\nHuFVWyJlJv7Hj7Mjoj9poivFeUkcEMPRXSyQigKd2tfe5ucrePUZlS07JDv3SAIDBIP7C8I9vV+n\nQRihbhdQH8d/nmjXWjDtXZXFyxWOn1CJjxUMGygICvR+vn7CSpwtn+PlQU5eCB2FBN88BIJmIgEh\nBMOehwMLjRJb3U7VP0niCKMb7uXFgawsqc4p2FUUxfGyQNoFZOKv2DlRHkCpZqFJzDYsWJzCN64o\npYwCCsmnwOv7qiQH75M4AVShEiQCXSammpy7mAaEyblDz+Ew4X6jhbXmiI36+MJtT9O/Yzu+2tia\nF2OGVBkFigJ+vnDlKNffOu5K8cOPCprsUJheMAuLWkKXZj8yotNbRC/9hfsnPFLvNAuOQ/5RcNch\nMeikwFIKdkdepo7K0WP1GBCAMu9nRFkBxAaiW9SqJDgdQV6FP2HdL/c8MSGMEsp1i5zr/DTN2OeG\n0gGjWJXQl6yUcAR28mjGkU0D6R/1Mn0DF6NIjQqszOMaPmVyzVnTVO7l1pF78DmYSOwewZ5BGnk1\nUxpqNIhSFLjpOmePkaIIunUSdOvktKsWUkrWbJD8sVri7weD+go6tRcN0l1oIuIIJogCCp0MiY5K\nW696Q4QEC64cdeoGToJowuDQX/k6wyiXrjQiBJJ4n3ya+ebihx89FCODNaIV3LEJVr5mGBI+wUbn\n2553GbmxlwUGsrykhLmF1Y26cu1+rMqrLZq9qmwLUTbvxKUAtmk7yaRhOhACQTDuy0JNLhxMA8Lk\n3GLsv2DoVbBzraFh0Kkv+PoTBrz1gsrnM3VWrZNICb27w8TxKjFRrr/Ie3QVqKqxdlYSkSJIWqNW\nLRx2zY+NB68lPbcVt1xym8fks0qsAZ72SqLZTlBxPDk1SkojwusfWVgskFUGiw6itIuCRkFGzCUl\nn932YfTp50UJ54T7Yed6KMozQhmVyR/Dr4Ek9yJe8/9P52RqqOMOjK+FYi2KJcveoMf2NHzef5ni\n7xexJy4RPVYBAWGh0LqZzpotAwkplCTuUciPlOTV9VxXqlALeO0ZhZaJsHOPpLxc0jpJ4O/n3UJc\nWKRzzyM66Zk15v27pH9veOx+FdXLsgNFKFyqDucPbRUnHEJFKiodRTs6Cg+hpjOIj7Bxo39nRMxm\nVuXFkVoWjI9ip1NAFqOCy2iudqa1SMJXVHtDwhJh9Ieux1OE4OWoKDr6+PDSyZNur5tZ4U+krf7q\nh8oQz34ONvjeJJJAEcB6bRMRIpymoonbnBKT8xvhKpnmXEYI0Q3YuHHjRrp1O4XSPZPznsq/WW+e\nOn/8RWfq544kSg26zFfxKTK+IOty08Q3SZz2gFdz+GwgHF1Rd6uOSjkPEIeqFDOt0xR+TrqLdpE5\nvPZB4/oHnTwZ3n23tsXjIH/mzwSPqyeBspLcLFgwA3ath4BgGHQ59LnYrUumNMvOq9ECKV19yes8\n2HYYgXuXV+VWFPuEUGQLI/yu8Xz1WyAzW/w/YpIV4ncIMlrC0fa6W1f0Uw8KPpgmOeloBmqzwT+u\nV7hqdP1P/Xc+aOdIqut9vboZRoSvT8O8AgWykDLKCCG4wYJJZ4IiWUyyPEiJLCVChNFcNK1V/thQ\njldUcNHRo273Xx+9g3jf2iEJCxY0NM5ET01HXzzH74YREkwQl6kj8BcNlws3OfNs2rSJ7t27A3SX\nUm46nbFMD4TJeUdD3NVjRyokNhXM/10nM0XiW+T6XEXYORo4nnp6WFZx9VfwXmuwlzqMGQyZ5iu5\nGX+yQYc7tzxIYWAQg/5zk3eDPvEEzJsHycmGkaSoCF2D7t0JphCKi43S0/oIjYRxk7y8EyiZ9iNS\nuu6ymsQCAnfXbqTkX5aHX0UBnywIZXarySAE6UmSzOaSiCPCXWQHgJf/Y7Q9r6S8HP77pU5kBAzq\n69qI0HXJmx9qbo0HgHWb4N5HND54XcFq8T6QHiQCCSKw/gPPEgHCn86iwxkbL9ZqpZ+fH2tKitFr\n/EMIJKGWUuJ8nPMZKkspbVi9yo2oSxyNsWIlhdSq0lCoNkcKKGSlto6LLEMaPLbJuY2ZsmJywdOx\nneCRSSovv2BBcfOQqaPi18YLL4GDkASYfBSad0kngeUM5AXuJYn2fFd1jASuS53C16VeZrFHRsKG\nDfD664iLLkJEORQ/N26E8eMhLg6WedcVsSEEL56OH67d3s1YglSdnzMWNLuF2a0fqOXV0FXIbC6N\nHE4Xj7IB/kZEpq7TUwiY9bN79aWfF0oWeaGEnJoGT7+suyxR/DvxcnQ0revIngerZVwZtcdtXhBw\nSsYDwDHSOExKLeOhJhJJijzGzPwsSl1lNZuct5gGhMnfBosvdBhnNB2qi2oVdLi+YeP5R8LNr69k\nYqMxDOVZQjlSa78AEg4f4eH+/eHwYe8GDQ6GLl2M49PrdDPMz4fRoyEvz+Wpp4paUcRAprjYI1GV\nClxZAz+1vBsh6ywGjsUp9ITjFB1EjYTXVi1dDoWUcCgFvvxWY89+6WQAzJnv/aKzeTvsO+D14Rck\nEarKd3Hx3BedzkXhB7g6ahf/jN1MmJedOc8GQsA7ORn8Iy2NYtOIuGAwDQiTvxWXvAXRDo+xYjVK\nGBUrXD3TMAgaTI8hiBAfj277yIwMmDjRu/Feew2GD4f9LkS1dB2KiuCbb05hoh4YOZI+vM1Anqd2\nCahkvf5/CBc5GZn+8UhX1QrCKGXtMk8h7rgg1Goku372jkKblu7DGxUV8M0PkslParz2no6mVxsR\nme5zAl1dntUbzAVKCMH4gI70DMyjmV+e17LWZwMpoVCzUqD5sLOsjK/zvWvyZXLuYxoQJhcGGRkw\nZowhyqQoEBEBb77p5C/3j4DbN8D1c6DfQ3DxG0Yoou1Vp3jdkAh49AkQwm0CmkXTjNBDqocgPsCx\nY/Doo253S2BH9EB+2B7P4uU6paUNd9Xbdcm8lAqe31zK1N1lZJXqcPvtiDatyaYV1Oh3YKUEgc5i\nngNgU+zFvNhvJg8OXYqvLDXyM+og0BkxPpMX8hQ+WakyY4aFZx62EBOlcMkwBVV1X15bKXm9ZIVk\nwaLqe2sS6/4cp+t7TsH4WxEkAhmrjqStaEUQgYQSQhQRf+ocpEMNc1VuE6Sj48eCGqWmJuc3ZhKl\nyflPXh506ACZNer7srPhwQfh6FF4661ahysWaDPW+DkjTLwPFH+0O+7FUlrm/rjcXEOy2h1z5zon\nCDgosgTxzIA57IgehMiQyPd0Avzh6f+n0rGdd0tmVqnOpfOKOFCsozhEI5/eWMrng/0ZuWoVe6MC\nQbMisDOMp+jNfyi3WNgT3pv72q5mX0wPhNSRQkEIiZSieoUAFGnH1yYZe3MMqotck5gowbOPKLz2\nnk5OPTpDs+fqjLrIeL657gqFV9/1zqugS+jb03wuqiRQBNBX7Vn1WpMa32hzKOXshjMq/yzy7D6s\nymvC7uJqSeqG9fQ0OZcxP2km5z9Tp9Y2Hmry9tuwbdvZn8PNt6GuW+9+f2goJCV5HkOvbG5kIZcm\n2GsoOf63y2vsijQ6flSKDhWXwNOvaBSX1DA67BWweTksnwsnUmoN/89fSjhQ6JD2Fka30XIdJi4r\nJtc/FKzG88QIHqUfr/Bdu8mMH3ucJ4f8wr4YQwK7MmwhpUAIQyG7kqYJKq887+tRMKtrR4UvP1B5\n9WmVlh5KXo6fgLx8476GDlC4c6KCv2t1aaDa6zDqYkGrFqYPwh2H5JGzbjwAaAhmZ7Tm07SutYwH\nBRge4FFIxeQ8wvRAmJz/zPHcTZNLLoEjRwzRgbOI6NgRxo0zchTqehKefRZ8PEgkl5cj9yezVk5i\nFQ9wA6MJ5jgApaofi5reWLu1OsYlSkph5VrJRUME7NsCr98PeTWSBgaNgTue5WSpyop8u/Mjg8OI\n+OFIOW1GlJE8t5ze/If5LW7nyw7PerxfKUGTglf+rRAZIWgc412JraoKOraD3t0EyQfdh2GWrZJc\nfqkx3tiRCpcOFxxOMdRHm8RBeqbOvN9g+y5JcBBcNFhhQB/TePDEqfS1qA8LKoNFfwooZK9Mxo5G\nFLEoWhQKWlVWjQLEWSxMCPbQWM7kvMI0IEzOfwLrqeM/cQJmzzYW97PNF18Ynob33oOcHEhMhCef\nhFtu8XzeuHGsnZPAQt6mO1OJZgeVWRXF1hDsqmvjQyiS7IxyePcjeOt541u6aQhEOvQils+FqFjW\nNbsT6c7fKCE5TfLQK1bC576Bip2v2z5aKzzhifi4U+tbMXyQ4KvvXRsQigLZubX3+dgErVtWv24U\nrfKvG1yPffyEZPo3Oms2SBDQv5fg5usVt6qlNZFSsn2XZPY8nWPHISYarhot6NpRaZAGybmI6qJl\ne0PoQRf2kkwBhQgEiaIpvZTu+AlDJbUDbauO7Rmn82VeHgsLC9GBEQEB/CMkhFDVVKW8UDANCJPz\nnzvvhN9/d7/fajW0FP4MA8Jmg+eeMzwO5eWevQ6VrF+P/sNPLMd4OmzBr7XadIWUZRBaeoJcX+fu\nhlIXtHzl/2DT59UnHDgJ7aKgQ4xhBCyYQfAdd2ArEZT7SucsQwVEqsKzvyrkjP4HazNacNLfQ66G\nAyEgsSmn3PSqUbQgIpwqVcqa6Dq0bO487slsydadEosqKSmFFWslJSVGaGTUJQIfm1H2OWOWxG6v\nPm/pSsnmbRrvv6p6DLFIKXntPY0lNVRGU9Ng41ZJUqLGS0+pBPifv0ZEc9GUffLU61zbqa3pSDvK\nKMeC6lE1M0hRuCssjLvCwk75eibnNmfNgBBCPA6MAroAZVLKcBfHNAGmAkOAAmA68KiUdQvMTUw8\ncOWVcOmlsGCB6/2aBo08txY+4wjhnfEAsGQJBUo8xboRK7bji+FKMNLNVKkzYdeLfNDtnVqnSUUS\nL1PouvV/jg01du7KhPhgCPWDogI6tyij2Swr+zqW124iKiE4W2HDaoEiJNI/gayEa73yPqgq3Dmx\n/qfJyif61RuMCfbtIejYzmiA9Y9xCm9+UPvjrigQ1wj6dBe1xpj+jc43c6TLPNPd+41whsXiuuxT\n1yEnDx6fonH9FQoDegssFuf7W7NBr2U81GT/QfjkS5377jh/n6BjRSNaiRZORoSKQhPiOIx7GWwr\nliqDwbeejqUmfw/OpgfCCnwLrAb+WXenEEIB5gPHgT5ALPAlUA48eRbnZXKhoSjsuWM+/uvG0CR7\nXu0HbCGMVeUGN77uc4HAQPz0kyhUoGNlJ9fRkZm1Dhmd/CF2xcK0rs9TIQOQQlLcrojX3xiMotmd\nxxRASp5hQIRFERgRwONDJS/8JjjaqpyyAImiQVSKhYQ9NqNvgWNh1hWr0bNc4taI8PUxmps1S/Bs\nZGi65I33dZaskFUJl3PmS4YOEDx0m52L0n6gpbaWtSmRzIuZwMmAJvTuDvfcqhqN0HSJqgiWrJB8\n/YP7fIlKA6E+38DhFHjlHZ25bWDKEyo+ttpn/DDfc2ns78sk//dPic16fnohhBD0V3rTVDbhkDyC\nHY1Y0YiWojkKCjO1WZRR7vLcwWLAnzxbk3Ods2ZASCmfBRBC/MPNIZcAbYChUsosYLsQ4ingZSHE\nM1JKF9+KJibOrH0XFkwSWMV3XMO1tGIeOgoCHeHnZyQ1nmkPRF4eLFxohCmGD4fGjSErC7Zsgago\n6NTJe/GCq6/Gdv/9dKz4im3cyF4uZxsT6MQMNFQEEgWdJJ+lZDx4gFI9DN1P55kXHiO0wENSnOZY\nDH2bQEUFY0faaNzIxpz5Kim7IDEewmMUftstnUWIK0WiPHgiLF58eyxdIVmywphHTT2qzb+foOT1\nEQSk7KG51UozTed68Qyln/0Pcf11fPWdzi+LJEXFRpjEWzEpb5Uxdu2FH3+RXDe2+t627dTZsdvz\neXYNSkrA9uf33TpjCCFoIuJoQpzTvuHqYH7VllT1xwCjKdYg0Y8E1fl4k783f2UORB9gu8N4qGQh\n8CHQHtj6l8zK5LyirAB+f8T4vUL6MZO5xLKOBFZSbgvjkn1XYosLObMX/d//0G6/k00hAzgS0o6Y\nx3+kd1w6tg2rqQq8d+oE334LrVvXPvfECSM/YvFi0E632wAAIABJREFUQ37x4ovh4Yfh1lu59MP7\nyaYlRxnAHD5nJ+PoqHxNc/1X/MRJskNDue67rwnKz2fUzz8Te/y4+zlKIMQHSirg3f9BahF8/z29\nuir06lqdTfn9Ty6aU9QgsugIWYHNnLaXV8DUaRovPOH5K+T3P3SEcL7EnZsn43ss2XhRUVHlOfC9\n9Sae3jqI9anVpX8HayuEnxGkhEV/6Fw31ngv0jMkT76oe3orAKOFedBf13vrrNNIRHOdOpYD8jAF\nspBQEUyiaI7tL+hUanLu81caEI2AOmL/Va8bYRoQJl6QuhrsJbW3HacXx+kF5dBuF7Q4kw9OW7Zw\n8vZHeHzQSlJC2qPodnTFQljJCV4IGEVinkNzYudOwzORnAy+vsaK9eST8NJLtVfTTz6B6dOhpARf\nIbhFDiSFgRynJ/6tQsh84Ck2v9uS6OIU4nftpaK8A8sjB7Ct3S2MEy/R/9iP7ue6MwOahBjpFLNm\nGYmkRhvfKvr1Enz6lfOpim6nc8YSnl5xFfdctJbUkHa19us6bNwGpaUSX1/3npaifM2pTbiPvYgB\nqbNRpbOkkKywE730e2j5f+7v6wxRVsNTP/c3nQovfJ4lpZB6HBLqzzE9b/EVvrQXbf7qaZicBzTI\ngBBCvAQ84uEQCbSVUu47rVl54YmcPHkyISG1nyzHjx/P+PHjT/PSJucTbqobq7D4nuELfvwxb/T6\njNSgVgBV2gx5PpE8M2A20+a3QpW64a8/dgx++AHGjyf39Y9Z/1UKF9V9xNUcPnEAaUhENWU5TVkO\n++Dhrwewq91jaChURfiFINM/nhf6f8+NO57lhoMvQ6mL1a/EDodyDHlGRYGlS50MiNhGgpuvU5j+\nrY6iV6ArVhRdI6Q0gwfX/QurXsZTq67nweF/UGhzzqbX3KU75+TAXXfReXdnDiTdX0vDwtde7NJ4\nAEOoKqi8HpnKM4CiQM8u1YbP9l3eBT/KyuCtqRpvvWAWsJmc+8ycOZOZM2vnU+WdwWZ8Df0UvA5M\nq+eYg16OdQLoWWdbjOP/dT0TTrz11lt069bNy0uZXKg06QcB0VCUSW2zUxjbm/Q9xYHLy40yg8rM\nv5wc2LyZjH0n2Rwz3OlwXbGQGdCUrVGD6ZaxxLFN5bepe5i3zc7xvdcwUd2EXViweJneowmVtidX\nsz16kLGhZj6CI0fhq/ZPcvGhaURxzPUgR/MMA0IAQUEuDxl/tUK75Z/w2xofcm2RdD+xgMv3f4Dq\nyIxoUrCHL+Ym8u+BP7MzqjqRLq4xrksapYRRo2DdOq6wLuPXZhMptIYYyZlAgV8kJ4ISiSk46JT0\nqEqNnZH9vXp/ThUhjNbi11xeHcop8LI9g5SwZz9kZkmiIs/PREqTvw+uHqo3bdpE9zoPEqdKg6Ss\npZQnpZT76vnxNvlxNdBRCFGzB+LFQB6wqyHzMvn7olrhiulGf4vKh1yhOrZ/Ub2tXnJy4Msv4Zpr\nIDbWKMG0WKqbc4WHw/DhRC76lrs33IWPvchpiP6ps2mftbrqtaJrZGeWsf+gJLIohX7HfvTaeABQ\npEahNbR6g4tkRonChsaXuh5AALkO2WKrFa5y0zFs9246//wKD62dyAvLR3Pl/veqjIfKYXztxTy1\n8hosWnWvjxMZsHajCxfE8uWwejVoGhGlabz1e38GpM7GqpVi1coY0Etie+Mlw3iocU86Cpujh7E9\naqDreZ4BFAHDBsA7L6m1RKW8CV/UpOSv64xtYnLOcDZ1IJoA4UBTQBVCdHbsSpZSFgG/YhgKXwoh\nHgEaA88D70kpK87WvEwuPFpeAnfvgg0fQU4yhCdB9zsgvIWXAzz4oNFwy1UGnb32yqIAow7+l8aF\nh3hyyC9V29tmreLxVeOo2ZNTAtfvfpWmeTvpnLEMXxdGRxV1Mg0rpRpu2vks5YoPvydOdHuecBMO\nQGI0vFAETJsGkS76laemQv/+UE+LZQWdTP8m6KI6n0HT4JlXdW64RnLjtTXyHLZsMYwuR2+P2KKD\nPLbmxqrdZc/t47ej15Az/ntGLH6WxunbKfMJZm7Tf/Flh2e8r145BUJC4L47Vax1NCDKXVcuuiQs\nFEKCJAuXSIqKoH0bQeuWpjfC5O/H2QzkPQfcXOP1Jsf/hwJ/SCl1IcRojKqLVUAR8Dnw9Fmck8kF\nSnhLuPi1Uzjxgw+Mtt8NQADdM34nKXsD+8ONJlNX730TiUCpYUAIQCDpe3xu1euaVB4pYmON8MLe\nvVXbK48NLcvkgQ23sS5uNPk+LgwAqRNR7CZ8ERAADzwAN98MLVu6Pua99wzjQau/R+KHXd9GF85O\ny6++lwwbKIlt5Jh1bGyV8eA0XVXlmU/D2JKqIxjLzMFjEbqduDiVo2lnfxHOyYU7HtAYNlAw5hKF\nkGDjmsGBkOfZhqpiUF/BTXfrVFRU2329u8Pjk9XzVh/CxORUOGvdOKWUt0gpVRc/f9Q45qiUcrSU\nMlBKGSOlfMRUoTTxRPJC+GoU/O9S2PGNoXd0Wjz//CmdJoEOmcsBsGqldMhcUcvtXxN3S4oANJuf\nUbGxYwe88ILL4wXw/9bc7NpDIhRymnZxfYGiIiNp0p3xALBypVfGQ4EtjF1R/av1Ieqwan2Nex89\n2tDCqNvzQFU5OuA6th4zwjLS8aMrlj/FeKgkLR1mzpbc+6hGdq6kpFQSHVX/eQBD+sPcXyUVDh9p\n5T/Juk0wc5b51WXy98Js521yXiAlfDYAvroUkufDgYUwaxy83x7spxOPzsg4pdMEcMu2x/l8bgu+\nnRNDSPlJj6VDrpZHHVCbNzVafVss4KFnQI/037jEby2+NapKVBVuvk7hojFudC6EqDJK3BId7bzQ\nO6h5P1o9XxXba2Yt+frCvHlG3kjlPAD69GFqz3fcai1Y/kSFaF2HzJM6HzywklduXclGL4vGl7qx\nt6Q0DIvU45LcfG/lrExMzm/MWiST84Jlz8HRlc7bT+6BXybBmI9PcWA/P+NJ/RSwSjsxxSkASEVB\nuHHbu0MB2LsHevWCNm2Mkk83SOD+/Q9zb+++7B19PyURcbRqKQgKFPDPA4YBUidfAykN7YeMDMNQ\ncMUttxidSl1QYAsnuDybQmsIv7S43XD3uPFApKTWWTR79oSjR2HuXDbvEnyfN4iD+aGUeqivCgmG\nkznu9595FFYW9WYIv3Axs/kVN0mmXlJYBLdNNqyLnl1h0m0KkRHmM5rJhYtpQJicF2z40P2+7TNP\nw4C46SaYOvUUT3YgBBue+YGQt54lKWdTvf0YnFi/3vjxdAmA1atR162j3dQPDBntQEd5Z3y825wD\npIQbb4Rff3W9f9QoeOQReOUVUFVDMkLXmJ94K+92ex8fvYRy1Q/pxnCopLQUZszS+W2pTnEJdG4v\nGH+VjeSIK3hzh3dP5CdzjB4bFRUe9CXOOIKlXMa/eBMfSijDD6iVA3pKrN8MN92lAzqKYghPTbhK\n0K+XgqqaeRImFwZC1qfdeo4hhOgGbNy4caOpA/E3YkoA2Itd7xMq/LtuGd6+ffCf/8DatUZS3+23\nG7H5upSWQt++RuXAqdChA3zwAfP2xrP1k9U8vvZPaNolBCQlwZ49xu+HDhmvPeUyHDgAiYnu9+/a\nBT/8wKwf7SwJvYwDYV1r7VYUCA2BbDcegpBgyC+ozglQFCMkYbcbMhQNpUMb2LGn4eedKqFk0pwD\nbKbPWb1OTBS8+oxKtKkhYfIXUUMHoruUclN9x3vC9K+ZnBdEJLnfF9q8zoY1a6BLF/j4Y8OFP38+\njBlj9KCoi68vrFtXHa+vDyGqcwbuvBO2bYOBA+nx/VN0y/gdO39CIF9Kw0Da41hhmzc3SlE98MQd\nh7j7YTtLV9Z5rC4shFdfNUIZP/5ImbRyPNB10qWfB1XPvPzaOZ66bmgreDIegl3rWgFGoqOn651p\n8glDc/zbCYxyz7NBeia8+m79SasmJucDpgFhcl5wydvu9136Vp0Nd99taA5X5gRUPpk/+ywcPuw8\nwKFDkJ3teQJCQIsWcMcdxvh//GGUgDoSBGOWfk+HzOVY+BMXh4oacim33OL2MB2FQ36tOORoZf3D\ntZ8aBtWbbxoaEI89ZhhR69czbuNTvLl4EH4VBbXH0CHLQ0dMV9IN9Tk3O7cXqG6+gU7mwCP3Ku7y\nOxtEaEj90hICnV0Y1SwS6NXV8/Gnw849kJZ+fnl+TUxcYRoQJucFzYfAVV+BrcZTqy0Ixk6DVjUj\nE2lpsGmT+wD23LlOm3Yd869/AlJCejp8+KERGhk4sPaqpOvEFSZ73U76tImLg/btq1+3aWPkM9RZ\ncTUUFjW9gRy/xlUL+nT9akoXLDG8Ftu21XqvFKmTkLeL0cnOeSFlbsSWTkX3SQho19p9roPVAl07\nC6a/rxLjJv/TW3Lz6jdmNKzYsaIocNN1guWrPR9/uuSeuXYEJiZ/GaYBYXLe0HECPJoHkw7CfUfg\nsXzoMvH0xpw2Q+PBqY3YFdkPTXh43K30QLgiORkUxSEcdepIwC68zGtu29ZQllQUo5JkzBh4+WVD\nilsxPtaasPBr84m81/39WqeWWgLZH+r+EVug0++Y+4oQp3nL+hfougzoIxg+SMHH5myAKAqMGCyw\nWQXh5DJt4A9c03ovXvTYOw0cnqQoWLtRUlrm/kiLBRrHuN9fH1brhd3N0+Tvg2lAmJxXCAFhzSE0\nwc0BjRtD165Vi6gTNRIp9x2QfPujsSi91eMjCmzh6FQLHNVCStd5BitWQLt2RsikPmJcrzoSKFN8\nWRU3lt+a3cyLfYz+2hXCgl7DJEkNTCK/5zBjBfv9d8jNNeZVWmp4Vjp2NPIiVq1iz1drGH95Ku/0\n/Ihyi1+t+2iat4PQ0lPTv6iLokDTeEOJ0VuaNNKYPHI/QdnJPPUg+NiqxwJo2wr+daMC774LjRsj\nrr+OvX+kcXrmmXekpcO+A56Psdvh4XuVUzYirrhMuG5CZmJynmGWcZpceLz/PgwfbuQI2O2GW1/T\n4N//hmbNqg5bvlpHVQw3empwG24buZMRh6fTLe1XOmStwE+rUfbxxBOQkGAkHEZGwtVXQ3Aw3HBD\n7VwET2RludwsUSi2BvNynxloqoXex36mTPXlwWF/cNK3EU0K9pPlF0u5xY9p81qB7qHz09atMHIk\nLXbuQVkSjqhRGdEqez0Prb2FJgV7PU5TorAi/mqvbql/b7jnXypbdkjXjbUctEkyDIUrY5bRa9MU\nxL8zAegeHc+MSU+zvKAXWdkSXQpiYyRlvy8nYNIkAA6GdGJ7zBCv5vNnUVQERW6qguqjbaszOxcT\nk78K04AwOX/R7XB0I+SmQEAkNO0DVj+jLHPzZiNXYfVqQyfh9tsNN38Nysqp9VBbaAtjTqv7mNPq\nPqz2En6aE2qsvu+8A7NmwZQphjGi60Yi5UMPQUqK9/N1U2apoBNWlkHPtPmsjr+CHZH9mZ94Gxcf\nmkZaQCKLmt1EgU8E1+x5HYvuRdennBysn/2XRyY9xtOv6GgVOmHFx3hp6SUuu4jW6oIuBMejO/FL\n0h1e3dKqdRDfWCe+sZG3ULerpRCGu//N51VE8nZ46oHa8Y7MY/i9dTfWcfP59scIysqMfYrszRVd\nXmX8zhc4Gtzaq7n8WVhUOHREJ7+g/mPrIgTs2gt9e5z5eZmY/NmYBoTJ+UlRFvz2PBScMIQgpAbr\nv4Ce90DLHtC6tVEl4YHunQU/LzQWrBY5m7lmz+u0ObmWHL9GLE28kedv2sjgMZEMWPQyynKj70WV\nEVBaWr9MdAO5a9N9hJae4JbtTxFQkYcmLKhS46adz/HEoHlEFTfAWFm1iq5PKHw6ZhG/PreMpnm7\n8LUX1mr2BYacdoZ/Apn+CVhUiT72KqIfv53wt30pPm7YV54yDzTN6CtRk8oGU4pi2Fv33aEihIC5\nXzh21vBUSMlBLZHX/hde6zq6UJndajKzk+6jfeYK7+/7T6B5U/h0xqmdKyVm+MLkgsE0IEzOT1Z+\nAIWOOH5lO+uyIlj4PNyeB+9/aCQaeqBHV0HnDiCXLOOFpSMRSCzSTlTxUdqeXMtPOXfxUsl/GJza\nn4e1D856wlBE6XHu3XQvYCzciqOrvY+9iMdXT+DbNg97N5AQVa27o959lgm7VrrNHlCA4PIcbhnt\nCPznwv0HFKa+Idi0VXLgkM70bxuWJCmlEa6IiYarO6TQccY0kDqZGcfI1DvQmKOEUV02+4u8AgW9\nSoeh9r0o7Irsi9DtSKGe1Vbf9REaAn26CxYsPr1kzqH9TQPC5MLATKI0Of8oOgnpO51bcaoKBPtC\nXjIMGFBvoyxVETz3sMKjByajSg2LNPzvlV01L0/+gCb5u1kWfy3rGl92Vm6lJqLGT615ohNVkkpa\nYHPKVL/6axGkhIkTjd/37/eYeqgjSA9oWmvbV7N0FAE9uyr07q42uMICoKxccixV460FCby2KIkn\nVg7g5rwveZDPmcBvPM3blOEDQAaNXRsPlbejWJGK5S81HgBKy2DrztMzHu67XSEm2jQgTC4MTAPC\n5PyjrJ7gc4AVcnKMRfShh+CLL6CkxOWhttxMwlK2o7hoxa2j0CNtAapewcr402u0VEVwcJV3oKFY\n9HKmdnmj/gPvvBOGDKGsXLK42ySmt3+a35veSKnq53SogmRO0r21tmVmQbHj7Tr1nhSiyihYkjCB\nTdEjahgACusYxGMYWhPNSEYR576wUmmpUaXREBpFQ1IijL5Y8Ol/VC4dbn7lmlw4mCEMk/OP4MZg\n8XXfx/tAtvEU/ssvRrljRQU89RQsW2bIPtfE4ukjINEUKxKBXbGembk//zxMmmQkdX72mef+FTXQ\nUBiQOpuBR7+vv5hx6lSOztvMoyMWkx38CGrbcjRh5ZPOr/DSsktonrfDGFOofNf6IX5tXlvF0tfH\n+AFongDhoZCd6/mSEonwNDMn74FgN505qiZx2fVN+PF74Vao6nzlxmvhhmvMr1iTCxfTHDY5/7D4\nQIcrnLfrEtanwvH86m2VJZapqTBiBJyso8ccEWGoSrrRTF4VNxZdsdAz7ZfaO2wqRPpDoM27OSsK\nPPkk3Ot42r/9dq+NBzDCGCOOfIWPXr/ehASmtP2Q3AKHoJRiqDUV2MJ5od+35FtCmdHmMW4afZgv\nOr1Qa3EXAi4bIao6Rqqq4K5/KUYLEKXudSTHE8vZOKKYtaOLKbc11F0hWHzZV8SMHclTD50Zt76i\nGH0s/qpoR1IiXDpM8M5Lqmk8mFzwmH/hJucnHa4wDIn1M0BUQKkdFh+AWdtdHy8lHDwI0dFw331G\n+2qrw6vw/vswcCCysBChadiFikVqfNbpRU76xdIucyUDU783jhVAp0aQFAGKY5XKKoI1qVDsQQ9C\n16Fbt+qVrUcPo8x08uRTk3L0wIHQLhwJ7eg8BcXC8aAkxl2RZuQUuKBnV7h5XG1LoX8vhTeeE/ww\nT+fgEUmjaBhzieCV/eWklFffc06MRvRR4dkTUQf/IBulpZJ3Pzkz93/FSMHoi41Ex3WbJOmZUOLG\nUeWKoEAoKDz162dkwuvPKdisZp6DyYWPaUCYnJ8IAW0vg6SLYdKd8PFnIIX7HhiV6Dq89ZYhP/3j\nj8Y4HTvCf/+LmDSJ8owcDoV0Ynbr+0gJbsfE7U9y+f73seqOhbJdNDQJhi1pkOrwdMQHQ594WHLI\nfc2josA338CVV1ZvmzTJeP399zBzJqxff9pvC0CBzXNnUVfGw8gRgsuGK7RMdL3wtW0laNuq2kuT\nWqSzdFdFrYzP9KYVRB918ZVSaRy5cAsM6a+wYLEk/cwIYzJ7nmTOL5K+PaB3D/jGe0VuAMpPM4yS\nV2BIYQ/sYxoQJhc+pgFhcn5jscAHn8Ddk2HBAiN5csqU+s/7+WdYsgSGDYO1a2HCBNA0bFLSOmc9\nj6250fkcRUDTEFh0CEorqo2FA9lwrACiAyDdWagJMAyXjAxjMV261DAaKipg5EjDkJg82TBkdu48\nbW9EYu5WVL0CzUPehqoC0kiSvOIywe03K4ZWg5esz7Q72Uo+pYpr74Obca+4DKIiBavWn9kOproO\nK9ed2rlnIg9j207JwD6nP46JybmOaUCYXBi0b1/dnfLgQeOJvj5GjjSkra1WY9Wpb+G2KbAtHUrq\nhCokxjb/ej5Ovr5GO/D//tfwSEhp/B4XB7/+anT6HDbMmEsD8iPqElJ+krH732V2q/tBVIcjBHDZ\nRTB0gMq6TTqqCv16uvc6eCJQFYSnqQSdVNGskqw4O7KeYVo0g4wsiIqAa8cqDO4nquZ1IbFl+7lf\nUWJicib4/+3deXhU1fnA8e97JxskYQ0h7KtQNksQWSxUUYpLLa22UtEKWBW1rlBBUaxrXQAXWsT6\nPCJqfxbtr7+6tC6IRUUoii0KgiAi+xJ2AiSyZc7vjzMxM8kkM3eW3Czv53nmkcycufMeb+beN2fV\nBELVPc8/bzfVevzxqssdPw7r1kV/3KMlZd0W4RyM0NleUmITBgjtatm+HXr3tl0qS5fawZbvvBN9\nXGH8euUUsini7/2mcrhIyMqEn53vcOnFdoBkr+/Z7ohvNhkWfuQnt4XQqztRtUIUFRvemC1025CB\nXwwCtPk6lS09jnMyxeA7SUhLhAg0bwozH/bhcyoev39fYeWXdeemu20nHD1myEiva6mRUqE0gVB1\nT1oaPPaY/St/xoz4j1e6GVckJRFuggcOlK3zXJ4xMHKkHVg5bJhtkYg0nqMyIvjOOZtLX76ZS5qm\nUFwMDRsScvM+fMTw4OMlrFxd9rb2beG+233kRVjo6MVX/GzYZP/tBDU7tF+Txp4+J2i5Kg1HbPeI\n49jHhOudsMkDwPaddSd5ALtXRkoVO8MrVVfoNE5Vd02bZverqGSKZlQcBzp3jj+WDh1sV0mkbpJb\nboHly2OL2XFg0iS7A+mCBdC8OT5HyM6Sspu3MfDll8y7+z+sWR3aFbNtB9zzaAkmQowLPjBhcxtH\n4Pou6cx6xMe5Zwv5fexsjaen++h3avhLjd9veH+J+6rWVI4DPzxDSEnR1gdV92kCoeouEbsN9549\nMH26HfPglt8PX38dXxwZGfDQQ1BQEF35zZuj3yI8mN9vu2ScSr7WS5fa/UF69WL8kwN44fWOnLV5\nXsjbt2yD1Wsr/whjDEcrWYrCcYQTR6FzR+Gma3w8NDWF68b5aNu68ptpiT/+mQ/xcBzIqXrSiit5\nuXD1r/SyquoH/U1XdV/TpnZJ67fesotJxdMi4ZaIvUtdfrkd3BmNvXvt4M5YVkP6z3/Ct3Js2WLr\nHpQMNT62m8mfjKXvroUhRXfvrbwFQkTo2T18aCUl0LuHu5hTU4Qunbxb+On2W+An5yXmMjjyPGH2\ndB9Nm2jrg6ofNIFQ9cvTT8e8F0VMjIHiYnfvKS6GrCzbcuHW9u22BaO8Z56BY8dCxlU4gF8cfrF2\nekjR9m2qvgGO+aUPkdCbvuNAl04wuL/7m+e4S6O/DCU60Zg2E0Ri3vDjO+lpMOaXDulpmjyo+iNp\nCYSI3CkiS0SkSET2V1LGX+5RIiKjkhWTUnTtCmvWwFlneR1J5XbsgFWr7AZgsdwxFy+u+NyqVWEH\ngvpMCZ0K7eqdjgN9ehBxWuepPYWHpzr06AaCoYHvBD9u+QWPXrw2pr7//n0d7r/DoWunyGUTfXsu\n8cOLr8R/nPFjHDIbavKg6pdkzsJIBf4KLAV+XUW5scA7lF0bImzbo1ScmjaFBhV3pqyRwnRHbGzc\nm52ZnWl7eB3tD4cZsHDFFfZ9V1xhWxz++U/48suwM0BKcNjVsCMAA/rBxOuj6945tZfDY31fw8z4\nFVKa6Mw0cOml8OKLZcuER6l/X4f+fR3Wb/Bz05TwLQKOA5Nvcpj1rJ8jlazXFYuTJ2N/r88Hv/2N\nMGyINuaq+idpCYQx5j4AERkboWihMWZPsuJQqgJj7C6dtczB9BY8eMYrrG4x9Lvn8gsWMGXpZWSf\nKJd3T5wIo0bBJZfYVTcr4cNPo7tu5s/jfOQ0c/EX9JYtcOmlSOlgz9LE5JVX7IJeU6dGf6wgXTs7\nTJ0ITz5TliT4fPCDgcL14xyaNBae/FP8XQ7xyEi3+dHA04TRFzu0ztOWB1U/1YR1IJ4SkTnABuBP\nxpi5Xgek6jhj4lrp0SsPnvEKa5qHrpG8IncY0we+wP2LfxpaeO9euwZGFckDKSlw1120mTDafVfJ\nCy+EX6fCGDvOJMYEAuAHAx1O7yesXmM4GRiY2SDDxrf/QOWzQKrDRRcK46/QRR6UAu8TiLuBhUAx\nMAKYLSKZxphZ3oal6jTHgfPOg/nza00isbFx75CWh1J+J4VPW19AQWZH8oo2hb748suVH9Dng61b\nIS/PfTBffQ5fvQfndoGi4/D1PthxuOz1XbvcH7OctFQh/9SKSU3xt3EfOmYd28PlP9euCqVKuUog\nRORh4PYqihighzEmqvWBjTHBux6tEJEsYBKgCYRKrkcegUWL4OjR+DrBq8nOzKoXs9qZ2Sk0gUhN\nhSNV7EtdUmK3Nnfrk/fgiYn231lp0DAVWmbBygJYu9cmZ6ee6v64UWrVEpo0goNVrCieSG1aQdMm\nMLi/w/nDy1pClFLuWyBmAJG6GKKc7B7WJ8BUEUkzxlS5vMyECRNo3LhxyHOjR49m9OjRcXy8qjd6\n94bPPrMLTC1YAAcP2qWma6i2h6vIyY2fNkfWhz7XrQP0bAj9e8HuI7BqN+wP+vM9I6PyBacqU3IS\nnnsodCBm6QqXvVvChgNwvATuvtvdcV3w+YRxlzlxjYNo1RLGjRYemWkiLgzatTPccbPXDbVKxWbe\nvHnMK7exYGFhYcKO7+qbYYzZB+xL2KdXlA8ciJQ8ADzxxBP069cviaGoOmffPjtL4P337V/gKSnQ\nujVs2xb7vhPVpP3hteQXLGBF7jD8TtnX1vGfZPD218kt3hr6hlYGxG/HNuRmwdlZsHBDWRIxfrz7\nILauh4OVjHd2BHq0g9segIsucn9sF84d5tD4T2gXAAAP8klEQVQwA+a85GdXDMOvR54n/HCwj7xc\nw1NzSlj3TeVlszJjj1Mpr4X7o3r58uWcdtppCTl+0lJrEWkHNAM6AD4R+X7gpfXGmCIRuRDIBT4G\njmHHQEwBpiUrJlWPrVgB/fuHdlecPGlnE9QSU5ZexvSBL/Bp6wvsE8bP4O2vM/HTq0MLts6GZkHT\nVB0Bv4FeufDRZujbF5o1s904O3fadSd69YJrrrFbi1fGiTB4cPbTcMZ5sVXOpaGDHYYOdvD7/azf\nCKvWGBo0EDp3gAce87Mv7MozduhHUZFtNenWRbhroo+xN1Q+DuaCc3TMg1KVSWbb3P3AmKCflwf+\nOwxYBJwAbgSewK4BsR641RjzbBJjUvWR3w8/+pH3Yx3OPBM+/DDmt2efOMj9i39KQWZHdmZ2os2R\n9RVbHsAmCuU5AtlpkJ4On38OK1eGtrq8+qqdtbFwIQwYED6Adl2hZTvYva3i+hRp6dB3SMx1i5Xj\nOHTrAt26lD339Ay44no/x8LM1igpgbZBOVJujvCDAbBkWcWyvXtA546aQChVmaR9O4wxVxpjfGEe\niwKvzzfG9DPGNDbGNAr8W5MHlXgffmg31EqWaKdA3nprQj4ur2gT+bvfD588tMqCxpUsgf3pdr67\nq5bvsikpsStfjh1b+Y6hInDtfeBLLWuNcHyAwFVToWFWTPVJtOxMh8surnhpcxxo0RwGnx56vibd\n5OPcs8uGhDgCZw+FB+/U6ZpKVUVHB6m6L9zeEIni80U/FfTGG5MXR6niE2UDG4MdOQ57IuzJ4ffD\n2rV2qe+ePcOX6XU6zPg7zH8ZtqyD3DYwfBR07R1/7An0i5FCUbHw6puGE4GGpy4d4Y5bfKSlhv7/\nSU8Tbr02hasuN+zdBznNITtLZ1soFYkmEKru69Urecd2s47Ejh3Ji6NU4TH4aBMM7WjHPYBNKPa6\nWPv52wiLLbTqAOOqms3tPccRrrzMxy9GGjZvhUbZ0L5t1UlBdpaQXTMaUZSqFTSBUHVf//4wZAgs\nWVJ583w4jmNnapw44e59lUnEMaKx8wh85QezD1Ic2F0E26JcOCEnB/r0SW581Sg7S+jdw+solKqb\ndISQqvtE4PXX4Sc/CX0+M7Ns/ILjhG6f3b07LF1qp3g+9JB9LZadMYcMSfwe1NHYcxCKs+GzguiS\nB1+gv3/GDEhLS25sSqk6QRMIVT80a2aTiO3bYdkyuybEkSOwf7/dqbKw0Dbd79lj95FYu9bORmjR\nAu64A/79b+gctBpkSgpcd13k5KBhw+preQi2Ywds3Bjy1K4G7flXv5s4lNYcgOMpGRTmnWJ3Jx06\nFN5+2w6iVEqpKGgXhqpfWre2j1JNmthHqZyc8O/Lz4d162zyceCA7RZp0cLuJ/Hmm5V/3qFDdupk\n+TmFPp9dbvro0djrEknQ+IyD6TlMGL6EwvQc6DyNxsf2UpTRFCcjnT8+4qNtax00qJRyR1sglIqW\n48CgQXD++TZ5AHg2wszjTp1gzpyy8RSOYx+NG9uukWryVpfxFGa0wO+k4HdSONAgj+OSzvET8Ld/\n1OxVOJVSNZO2QCgVj7w8GDEC3n03/OvjxtnX+/WD556zXSj5+XDllba1Y/NmmDkz6WGuyhmCXyqu\na+D3w8rVHnSxKKVqPU0glIrXG2/AwIF2uexgv/2tXQEToEcPu3FXeXffDbNn25keSZR1/CCO/2TI\nPhpgl4DVqYtKqVhoF4ZS8UpPh+XLYf58u9rk5Mnw6ad2RkOkQZbNm8NNNyUvtsDsiuFbX6qQPAAY\nYMQwvQwopdzTFgilEsFxbFfFiBHu33vffbYVIhkDKi+8ENas4fRT4Ge9tvLa6nb4HEDsGMuhg4Tz\nztYBlEop9zSBUMprWVl2QOXEiYk9bs+e8NprgO2quBY4Z4Nh8TI/JSdhQD+H3j1AvFinQilV62kC\noVRNMGGCHZA5bVrFnTJjFWZwZtfOQtfOukmUUip+2vmpVE0xejR89pldM2LMmPiONWkSDB+emLiU\nUioMTSCUqmlSUmDuXDtzwwUD0LGjnRUybVoyIlNKqe9oAqFUTeQ48N57cOaZUb9FgJ2n/7jinh9K\nKZUEmkAoVVO1bg0ffGCX0B4/PmJxAyxZ1YB9+3VhKKVU8mkCoVRNd8opMGtW6G6hldia1Z2FH2kC\noZRKPk0glKoNUlPh3nsrfbkEh4PpuSzueAkHCjWBUEolnyYQStUWkybZRacyM4HAoMmAbY26c8dZ\n71IsmXTtpOs6KKWST9eBUKq2cBz43e/gttv479++4pmXfDQ/VsChtGZsaPJ9HJ/QqgUMGaQJhFIq\n+TSBUKq2adiQ08bkM6qDn+df7sm+/XbLjQH94IarfKSlagKhlEo+TSCUqqWGn+kwbKiwbz80yIDs\nLE0clFLVRxMIpWoxnyPk5ngdhVKqPtJBlEoppZRyTRMIpZRSSrmmCYRSSimlXNMEogabN2+e1yFU\nC61n3aL1rHvqS13rSz0TJWkJhIh0EJFnRWSDiBSLyNcicq+IpJYrd6qILBKRb0Vks4hMSlZMtU19\n+WXWetYtWs+6p77Utb7UM1GSOQvje9gNAq8BvgF6A88CDYHJACKSDcwH3gWuBfoAc0XkgDHm2STG\nppRSSqk4JC2BMMbMxyYHpTaJyAzgOgIJBPArIBW4yhhzElgjIvnARGyyoZRSSqkaqLrHQDQB9gf9\nPAhYFEgeSs0HuotI42qNTCmllFJRq7aFpESkK3AjtnWhVB6woVzRXUGvFYY5VAbAmjVrEh1ijVNY\nWMjy5cu9DiPptJ51i9az7qkvda0P9Qy6d2bEeywxxt3WvyLyMHB7FUUM0MMYsy7oPW2AD4CFxphr\ng56fD2wwxlwf9FxP4Ivyxwh6/TLgJVdBK6WUUirY5caYv8RzgFhaIGYAcyOU+a5VQURaAwuBxcHJ\nQ0AB0LLcc7mB/+4ivPnA5cAm4GgU8SqllFLKygA6EjpGMSauWyBcHdy2PCwEPgWuMOU+TESuAx4E\nWhpjSgLPPQT8zBjTM2mBKaWUUiouSUsgRKQVsAjbUjAWKCl9zRizK1CmEbAWWAA8ip3GOQe4xRgz\nJymBKaWUUipuyUwgxgLPlX8aMMYYX1C5PsAs4HRgL/AHY8yMpASllFJKqYRIaheGUkoppeom3QtD\nKaWUUq5pAqGUUkop12pNAlGfNucSkTtFZImIFInI/krK+Ms9SkRkVHXHGo8o69lORN4MlCkQkWki\nUmt+b8MRkU1hzt3kyO+s+UTkBhHZGPj+fSwip3sdUyKJyD1hvntfeh1XvERkqIi8ISLbA3UaGabM\n/SKyI3D9XRBYHLBWiVRPEZkb5vy+5VW8sRKRKSKyTEQOicguEXlVRLqVK5MuIk+JyF4ROSwifxOR\n3MqOGU5tuhAHb87VE5iA3Vfj96UFgjbn2gj0AyYB94rI1dUebXxSgb8CT0coNxa7jkYe0Ap4Lclx\nJVqV9QwkCm9h1ysZhK3vOOD+aoovWQwwldBz90dPI0oAEfkl8BhwD5APrADmi0iOp4El3irKzl0e\nMMTbcBIiE/gcuAH7+xlCRG7HriR8LTAAKMKe27TqDDIBqqxnwNuEnt/R1RNaQg3FXlMGAsOx19p3\nRaRBUJkngR8DPwd+CLQG/s/Vpxhjau0DuA1YH/Tz9diZHClBzz0MfOl1rDHWbyywv5LX/MBIr2NM\nZj2B84ETQE7Qc9cCB4LPcW17YBPcm72OIwn1+hiYGfSzANuAyV7HlsA63gMs9zqOJNexwrUF2AFM\nCPq5EfAtMMrreBNcz7nA372OLQl1zQnUd0jQ+TsGXBRUpnugzIBoj1ubWiDCqe+bcz0lIntE5BMR\nudLrYJJgEPCFMWZv0HPzgcZAL29CSpg7Ak2Hy0XkNhHxRX5LzRXoSjwN+Ffpc8Zeld4DBnsVV5Kc\nEmgC/0ZE/kdE2nkdUDKJSCfsX+LB5/YQ8Al179wCnBVo9l8rIrNFpJnXASVAE2yLS+n98jRsy27w\nOf0K2IKLc1ptm2klWgI356qt7sau8lkMjABmi0imMWaWt2ElVB4VlzQPPp8rqjechJkJLMd+mc8A\nHsHW5zYvg4pTDuAj/PnqXv3hJM3H2G60r7BdT/cCi0SktzGmyMO4kikPe/MJd27zqj+cpHob24y/\nEeiCbcF+S0QGBxLiWkdEBNtdsdgYUzpeJw84HkgEg7k6p54nEHFszvU28IoxpvxiVRU+Iug4noml\nnlUxxvw+6McVIpKFHfPhaQKR6HpGOE6N4abexpgng55fJSIngD+JyBRjzImkBlr9hBp2ruJhjAne\nP2CViCwDNgOjiLxHUF1Tp84tgDHmr0E/rhaRL4BvgLOA9z0JKn6zseMGoxmr4+qcep5A4P3mXNXF\nVT1j8AkwVUTSjDHH4zhOvBJZzwLsCqXBSs+v1+ezvHjq/Qn2u9gR+DqBMVWnvdjl6sN9/2rauUoY\nY0yhiKwDat2MBBcKsDeWloSey1zgM08iqibGmI0ishd7fmtdAiEis4ALgKHGmB1BLxUAaSLSqFwr\nhKvvq+cJhDFmH7AvmrISujnXr8MUWQo8KCI+E9icC9u8/5UxxtPuCzf1jFE+cMDj5CHR9VwK3Cki\nOUHjIEZgu6Jq1NS5OOudjx28tDtxEVUvY8wJEfkvcA7wBnzXdHoO8AcvY0umQMtfF+BFr2NJlsBN\ntAB7LlfCd/sYDQSe8jK2ZBORtkBzYKfXsbgVSB5+CpxpjNlS7uX/Aiex5/TVQPluQHvsdTcqnicQ\n0RK7OdcH2M25JgO59vpUtjkX8Bfgd8BzIlK6OdfNwC3VHG5cAoOymgEdAJ+IfD/w0npjTJGIXIjN\nFD/GjqQdAUwBpnkRb6wi1RN4F5so/DkwjawV8AAwq7Y29YvIIOyF933gMHYMxOPAn71OchPgceCF\nQCKxDDvVuiHwvJdBJZKITAf+ge22aAPch70Qz/MyrniJSCb2r+zSLt/Oge/jfmPMVmwf+lQRWY+9\nBj+AnWHzugfhxqyqegYe92DHQBQEyj0KrCMBW19XJxGZjZ1+OhIoEpHSlsFCY8xRY8whEZkDPC4i\nB7DXoj8AS4wxy6L+IK+nl7iYhlK6o2fwww+UlCvXB/gQO7hwC3Cb17HHUNe5YepaAvww8Pq52EF4\nhcChwL+v9jruRNczUKYd8E/gCLZp7VHA8Tr2OOqcj83w92Pn0q/CJsSpXseWoPr9BnuD+TZQz/5e\nx5Tg+s3D3ji/DVxf/gJ08jquBNTrzNLrabnHc0Fl7sVO5yzG3lC7eh13IusJZADvYJOHo9gux6eB\nFl7HHUM9w9WxBBgTVCYdu1bEXmwC8b9ArpvP0c20lFJKKeVabV8HQimllFIe0ARCKaWUUq5pAqGU\nUkop1zSBUEoppZRrmkAopZRSyjVNIJRSSinlmiYQSimllHJNEwillFJKuaYJhFJKKaVc0wRCKaWU\nUq5pAqGUUkop1/4fWGfLoxA8oZIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe0fa0b0e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_scatter(transfer_values_reduced, cls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## TensorFlow中的新分类器"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在我们将会在TensorFlow中创建一个新的神经网络。这个网络会把Inception模型中的transfer-values作为输入，然后输出CIFAR-10图像的预测类别。\n",
    "\n",
    "这里假定你已经熟悉如何在TensorFlow中建立神经网络，否则请阅读教程#03。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 占位符 （Placeholder）变量"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "首先需要找到transfer-values的数组长度，它是保存在Inception模型对象中的一个变量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "transfer_len = model.transfer_len"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在为输入的transfer-values创建一个placeholder变量，输入到我们新建的网络中。变量的形状是`[None, transfer_len]`，`None`表示它的输入数组包含任意数量的样本，每个样本元素个数为2048，即`transfer_len`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x = tf.placeholder(tf.float32, shape=[None, transfer_len], name='x')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "为输入图像的真实类型标签定义另外一个placeholder变量。这是One-Hot编码的数组，包含10个元素，每个元素代表了数据集中的一种可能类别。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_true = tf.placeholder(tf.float32, shape=[None, num_classes], name='y_true')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算代表真实类别的整形数字。这也可能是一个placeholder变量。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_true_cls = tf.argmax(y_true, dimension=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 神经网络"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建在CIFAR-10数据集上做分类的神经网络。它将Inception模型得到的transfer-values作为输入，保存在placeholder变量`x`中。网络输出预测的类别`y_pred`。\n",
    "\n",
    "教程#03中有更多使用Pretty Tensor构造神经网络的细节。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Wrap the transfer-values as a Pretty Tensor object.\n",
    "x_pretty = pt.wrap(x)\n",
    "\n",
    "with pt.defaults_scope(activation_fn=tf.nn.relu):\n",
    "    y_pred, loss = x_pretty.\\\n",
    "        fully_connected(size=1024, name='layer_fc1').\\\n",
    "        softmax_classifier(num_classes=num_classes, labels=y_true)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 优化方法"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建一个变量来记录当前优化迭代的次数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "global_step = tf.Variable(initial_value=0,\n",
    "                          name='global_step', trainable=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "优化新的神经网络的方法。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "optimizer = tf.train.AdamOptimizer(learning_rate=1e-4).minimize(loss, global_step)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 分类准确率"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "网络的输出y_pred是一个包含10个元素的数组。类别号是数组中最大元素的索引。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "y_pred_cls = tf.argmax(y_pred, dimension=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "创建一个布尔向量，表示每张图像的真实类别是否与预测类别相同。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "correct_prediction = tf.equal(y_pred_cls, y_true_cls)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将布尔值向量类型转换成浮点型向量，这样子False就变成0，True变成1，然后计算这些值的平均数，以此来计算分类的准确度。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 运行TensorFlow"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 创建TensorFlow会话（session）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一旦创建了TensorFlow图，我们需要创建一个TensorFlow会话，用来运行图。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "session = tf.Session()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 初始化变量"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们需要在开始优化weights和biases变量之前对它们进行初始化。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "session.run(tf.global_variables_initializer())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 获取随机训练batch的帮助函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "训练集中有50,000张图像（以及保存transfer-values的数组）。用这些图像（transfer-vlues）计算模型的梯度会花很多时间。因此，我们在优化器的每次迭代里只用到了一小部分的图像（transfer-vlues）。\n",
    "\n",
    "如果内存耗尽导致电脑死机或变得很慢，你应该试着减少这些数量，但同时可能还需要更优化的迭代。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_batch_size = 64"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "函数用来从训练集中选择随机batch的transfer-vlues。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def random_batch():\n",
    "    # Number of images (transfer-values) in the training-set.\n",
    "    num_images = len(transfer_values_train)\n",
    "\n",
    "    # Create a random index.\n",
    "    idx = np.random.choice(num_images,\n",
    "                           size=train_batch_size,\n",
    "                           replace=False)\n",
    "\n",
    "    # Use the random index to select random x and y-values.\n",
    "    # We use the transfer-values instead of images as x-values.\n",
    "    x_batch = transfer_values_train[idx]\n",
    "    y_batch = labels_train[idx]\n",
    "\n",
    "    return x_batch, y_batch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 执行优化迭代的帮助函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "函数用来执行一定数量的优化迭代，以此来逐渐改善网络层的变量。在每次迭代中，会从训练集中选择新的一批数据，然后TensorFlow在这些训练样本上执行优化。每100次迭代会打印出进度。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def optimize(num_iterations):\n",
    "    # Start-time used for printing time-usage below.\n",
    "    start_time = time.time()\n",
    "\n",
    "    for i in range(num_iterations):\n",
    "        # Get a batch of training examples.\n",
    "        # x_batch now holds a batch of images (transfer-values) and\n",
    "        # y_true_batch are the true labels for those images.\n",
    "        x_batch, y_true_batch = random_batch()\n",
    "\n",
    "        # Put the batch into a dict with the proper names\n",
    "        # for placeholder variables in the TensorFlow graph.\n",
    "        feed_dict_train = {x: x_batch,\n",
    "                           y_true: y_true_batch}\n",
    "\n",
    "        # Run the optimizer using this batch of training data.\n",
    "        # TensorFlow assigns the variables in feed_dict_train\n",
    "        # to the placeholder variables and then runs the optimizer.\n",
    "        # We also want to retrieve the global_step counter.\n",
    "        i_global, _ = session.run([global_step, optimizer],\n",
    "                                  feed_dict=feed_dict_train)\n",
    "\n",
    "        # Print status to screen every 100 iterations (and last).\n",
    "        if (i_global % 100 == 0) or (i == num_iterations - 1):\n",
    "            # Calculate the accuracy on the training-batch.\n",
    "            batch_acc = session.run(accuracy,\n",
    "                                    feed_dict=feed_dict_train)\n",
    "\n",
    "            # Print status.\n",
    "            msg = \"Global Step: {0:>6}, Training Batch Accuracy: {1:>6.1%}\"\n",
    "            print(msg.format(i_global, batch_acc))\n",
    "\n",
    "    # Ending time.\n",
    "    end_time = time.time()\n",
    "\n",
    "    # Difference between start and end-times.\n",
    "    time_dif = end_time - start_time\n",
    "\n",
    "    # Print the time-usage.\n",
    "    print(\"Time usage: \" + str(timedelta(seconds=int(round(time_dif)))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 展示结果的帮助函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 绘制错误样本的帮助函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "函数用来绘制测试集中被误分类的样本。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_example_errors(cls_pred, correct):\n",
    "    # This function is called from print_test_accuracy() below.\n",
    "\n",
    "    # cls_pred is an array of the predicted class-number for\n",
    "    # all images in the test-set.\n",
    "\n",
    "    # correct is a boolean array whether the predicted class\n",
    "    # is equal to the true class for each image in the test-set.\n",
    "\n",
    "    # Negate the boolean array.\n",
    "    incorrect = (correct == False)\n",
    "    \n",
    "    # Get the images from the test-set that have been\n",
    "    # incorrectly classified.\n",
    "    images = images_test[incorrect]\n",
    "    \n",
    "    # Get the predicted classes for those images.\n",
    "    cls_pred = cls_pred[incorrect]\n",
    "\n",
    "    # Get the true classes for those images.\n",
    "    cls_true = cls_test[incorrect]\n",
    "\n",
    "    n = min(9, len(images))\n",
    "    \n",
    "    # Plot the first n images.\n",
    "    plot_images(images=images[0:n],\n",
    "                cls_true=cls_true[0:n],\n",
    "                cls_pred=cls_pred[0:n])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 绘制混淆（confusion）矩阵的帮助函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import a function from sklearn to calculate the confusion-matrix.\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "def plot_confusion_matrix(cls_pred):\n",
    "    # This is called from print_test_accuracy() below.\n",
    "\n",
    "    # cls_pred is an array of the predicted class-number for\n",
    "    # all images in the test-set.\n",
    "\n",
    "    # Get the confusion matrix using sklearn.\n",
    "    cm = confusion_matrix(y_true=cls_test,  # True class for test-set.\n",
    "                          y_pred=cls_pred)  # Predicted class.\n",
    "\n",
    "    # Print the confusion matrix as text.\n",
    "    for i in range(num_classes):\n",
    "        # Append the class-name to each line.\n",
    "        class_name = \"({}) {}\".format(i, class_names[i])\n",
    "        print(cm[i, :], class_name)\n",
    "\n",
    "    # Print the class-numbers for easy reference.\n",
    "    class_numbers = [\" ({0})\".format(i) for i in range(num_classes)]\n",
    "    print(\"\".join(class_numbers))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 计算分类的帮助函数\n",
    "\n",
    "这个函数用来计算图像的预测类别，同时返回一个代表每张图像分类是否正确的布尔数组。  \n",
    "\n",
    "由于计算可能会耗费太多内存，就分批处理。如果你的电脑死机了，试着降低batch-size。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Split the data-set in batches of this size to limit RAM usage.\n",
    "batch_size = 256\n",
    "\n",
    "def predict_cls(transfer_values, labels, cls_true):\n",
    "    # Number of images.\n",
    "    num_images = len(transfer_values)\n",
    "\n",
    "    # Allocate an array for the predicted classes which\n",
    "    # will be calculated in batches and filled into this array.\n",
    "    cls_pred = np.zeros(shape=num_images, dtype=np.int)\n",
    "\n",
    "    # Now calculate the predicted classes for the batches.\n",
    "    # We will just iterate through all the batches.\n",
    "    # There might be a more clever and Pythonic way of doing this.\n",
    "\n",
    "    # The starting index for the next batch is denoted i.\n",
    "    i = 0\n",
    "\n",
    "    while i < num_images:\n",
    "        # The ending index for the next batch is denoted j.\n",
    "        j = min(i + batch_size, num_images)\n",
    "\n",
    "        # Create a feed-dict with the images and labels\n",
    "        # between index i and j.\n",
    "        feed_dict = {x: transfer_values[i:j],\n",
    "                     y_true: labels[i:j]}\n",
    "\n",
    "        # Calculate the predicted class using TensorFlow.\n",
    "        cls_pred[i:j] = session.run(y_pred_cls, feed_dict=feed_dict)\n",
    "\n",
    "        # Set the start-index for the next batch to the\n",
    "        # end-index of the current batch.\n",
    "        i = j\n",
    "        \n",
    "    # Create a boolean array whether each image is correctly classified.\n",
    "    correct = (cls_true == cls_pred)\n",
    "\n",
    "    return correct, cls_pred"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "计算测试集上的预测类别。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def predict_cls_test():\n",
    "    return predict_cls(transfer_values = transfer_values_test,\n",
    "                       labels = labels_test,\n",
    "                       cls_true = cls_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 计算分类准确率的帮助函数\n",
    "\n",
    "这个函数计算了给定布尔数组的分类准确率，布尔数组表示每张图像是否被正确分类。比如， `cls_accuracy([True, True, False, False, False]) = 2/5 = 0.4`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def classification_accuracy(correct):\n",
    "    # When averaging a boolean array, False means 0 and True means 1.\n",
    "    # So we are calculating: number of True / len(correct) which is\n",
    "    # the same as the classification accuracy.\n",
    "\n",
    "    # Return the classification accuracy\n",
    "    # and the number of correct classifications.\n",
    "    return correct.mean(), correct.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 展示分类准确率的帮助函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "函数用来打印测试集上的分类准确率。\n",
    "\n",
    "为测试集上的所有图片计算分类会花费一段时间，因此我们直接从这个函数里调用上面的函数，这样就不用每个函数都重新计算分类。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def print_test_accuracy(show_example_errors=False,\n",
    "                        show_confusion_matrix=False):\n",
    "\n",
    "    # For all the images in the test-set,\n",
    "    # calculate the predicted classes and whether they are correct.\n",
    "    correct, cls_pred = predict_cls_test()\n",
    "    \n",
    "    # Classification accuracy and the number of correct classifications.\n",
    "    acc, num_correct = classification_accuracy(correct)\n",
    "    \n",
    "    # Number of images being classified.\n",
    "    num_images = len(correct)\n",
    "\n",
    "    # Print the accuracy.\n",
    "    msg = \"Accuracy on Test-Set: {0:.1%} ({1} / {2})\"\n",
    "    print(msg.format(acc, num_correct, num_images))\n",
    "\n",
    "    # Plot some examples of mis-classifications, if desired.\n",
    "    if show_example_errors:\n",
    "        print(\"Example errors:\")\n",
    "        plot_example_errors(cls_pred=cls_pred, correct=correct)\n",
    "\n",
    "    # Plot the confusion matrix, if desired.\n",
    "    if show_confusion_matrix:\n",
    "        print(\"Confusion Matrix:\")\n",
    "        plot_confusion_matrix(cls_pred=cls_pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 结果"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 优化之前的性能"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "测试集上的准确度很低，这是由于模型只做了初始化，并没做任何优化，所以它只是对图像做随机分类。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on Test-Set: 9.4% (939 / 10000)\n"
     ]
    }
   ],
   "source": [
    "print_test_accuracy(show_example_errors=False,\n",
    "                    show_confusion_matrix=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 10,000次优化迭代后的性能"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在10,000次优化迭代之后，测试集上的分类准确率大约为90%。相比之下，之前教程#06中的准确率低于80%。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Global Step:    100, Training Batch Accuracy:  82.8%\n",
      "Global Step:    200, Training Batch Accuracy:  90.6%\n",
      "Global Step:    300, Training Batch Accuracy:  90.6%\n",
      "Global Step:    400, Training Batch Accuracy:  95.3%\n",
      "Global Step:    500, Training Batch Accuracy:  85.9%\n",
      "Global Step:    600, Training Batch Accuracy:  84.4%\n",
      "Global Step:    700, Training Batch Accuracy:  90.6%\n",
      "Global Step:    800, Training Batch Accuracy:  93.8%\n",
      "Global Step:    900, Training Batch Accuracy:  92.2%\n",
      "Global Step:   1000, Training Batch Accuracy:  95.3%\n",
      "Global Step:   1100, Training Batch Accuracy:  93.8%\n",
      "Global Step:   1200, Training Batch Accuracy:  90.6%\n",
      "Global Step:   1300, Training Batch Accuracy:  95.3%\n",
      "Global Step:   1400, Training Batch Accuracy:  90.6%\n",
      "Global Step:   1500, Training Batch Accuracy:  90.6%\n",
      "Global Step:   1600, Training Batch Accuracy:  92.2%\n",
      "Global Step:   1700, Training Batch Accuracy:  90.6%\n",
      "Global Step:   1800, Training Batch Accuracy:  92.2%\n",
      "Global Step:   1900, Training Batch Accuracy:  84.4%\n",
      "Global Step:   2000, Training Batch Accuracy:  85.9%\n",
      "Global Step:   2100, Training Batch Accuracy:  87.5%\n",
      "Global Step:   2200, Training Batch Accuracy:  90.6%\n",
      "Global Step:   2300, Training Batch Accuracy:  92.2%\n",
      "Global Step:   2400, Training Batch Accuracy:  95.3%\n",
      "Global Step:   2500, Training Batch Accuracy:  89.1%\n",
      "Global Step:   2600, Training Batch Accuracy:  93.8%\n",
      "Global Step:   2700, Training Batch Accuracy:  87.5%\n",
      "Global Step:   2800, Training Batch Accuracy:  90.6%\n",
      "Global Step:   2900, Training Batch Accuracy:  92.2%\n",
      "Global Step:   3000, Training Batch Accuracy:  96.9%\n",
      "Global Step:   3100, Training Batch Accuracy:  96.9%\n",
      "Global Step:   3200, Training Batch Accuracy:  92.2%\n",
      "Global Step:   3300, Training Batch Accuracy:  95.3%\n",
      "Global Step:   3400, Training Batch Accuracy:  93.8%\n",
      "Global Step:   3500, Training Batch Accuracy:  89.1%\n",
      "Global Step:   3600, Training Batch Accuracy:  89.1%\n",
      "Global Step:   3700, Training Batch Accuracy:  95.3%\n",
      "Global Step:   3800, Training Batch Accuracy:  98.4%\n",
      "Global Step:   3900, Training Batch Accuracy:  89.1%\n",
      "Global Step:   4000, Training Batch Accuracy:  92.2%\n",
      "Global Step:   4100, Training Batch Accuracy:  96.9%\n",
      "Global Step:   4200, Training Batch Accuracy: 100.0%\n",
      "Global Step:   4300, Training Batch Accuracy: 100.0%\n",
      "Global Step:   4400, Training Batch Accuracy:  90.6%\n",
      "Global Step:   4500, Training Batch Accuracy:  95.3%\n",
      "Global Step:   4600, Training Batch Accuracy:  96.9%\n",
      "Global Step:   4700, Training Batch Accuracy:  96.9%\n",
      "Global Step:   4800, Training Batch Accuracy:  96.9%\n",
      "Global Step:   4900, Training Batch Accuracy:  92.2%\n",
      "Global Step:   5000, Training Batch Accuracy:  98.4%\n",
      "Global Step:   5100, Training Batch Accuracy:  93.8%\n",
      "Global Step:   5200, Training Batch Accuracy:  92.2%\n",
      "Global Step:   5300, Training Batch Accuracy:  98.4%\n",
      "Global Step:   5400, Training Batch Accuracy:  98.4%\n",
      "Global Step:   5500, Training Batch Accuracy: 100.0%\n",
      "Global Step:   5600, Training Batch Accuracy:  92.2%\n",
      "Global Step:   5700, Training Batch Accuracy:  98.4%\n",
      "Global Step:   5800, Training Batch Accuracy:  92.2%\n",
      "Global Step:   5900, Training Batch Accuracy:  92.2%\n",
      "Global Step:   6000, Training Batch Accuracy:  93.8%\n",
      "Global Step:   6100, Training Batch Accuracy:  95.3%\n",
      "Global Step:   6200, Training Batch Accuracy:  98.4%\n",
      "Global Step:   6300, Training Batch Accuracy:  98.4%\n",
      "Global Step:   6400, Training Batch Accuracy:  96.9%\n",
      "Global Step:   6500, Training Batch Accuracy:  95.3%\n",
      "Global Step:   6600, Training Batch Accuracy:  96.9%\n",
      "Global Step:   6700, Training Batch Accuracy:  96.9%\n",
      "Global Step:   6800, Training Batch Accuracy:  92.2%\n",
      "Global Step:   6900, Training Batch Accuracy:  96.9%\n",
      "Global Step:   7000, Training Batch Accuracy: 100.0%\n",
      "Global Step:   7100, Training Batch Accuracy:  95.3%\n",
      "Global Step:   7200, Training Batch Accuracy:  96.9%\n",
      "Global Step:   7300, Training Batch Accuracy:  96.9%\n",
      "Global Step:   7400, Training Batch Accuracy:  95.3%\n",
      "Global Step:   7500, Training Batch Accuracy:  95.3%\n",
      "Global Step:   7600, Training Batch Accuracy:  93.8%\n",
      "Global Step:   7700, Training Batch Accuracy:  93.8%\n",
      "Global Step:   7800, Training Batch Accuracy:  95.3%\n",
      "Global Step:   7900, Training Batch Accuracy:  95.3%\n",
      "Global Step:   8000, Training Batch Accuracy:  93.8%\n",
      "Global Step:   8100, Training Batch Accuracy:  95.3%\n",
      "Global Step:   8200, Training Batch Accuracy:  98.4%\n",
      "Global Step:   8300, Training Batch Accuracy:  93.8%\n",
      "Global Step:   8400, Training Batch Accuracy:  98.4%\n",
      "Global Step:   8500, Training Batch Accuracy:  96.9%\n",
      "Global Step:   8600, Training Batch Accuracy:  96.9%\n",
      "Global Step:   8700, Training Batch Accuracy:  98.4%\n",
      "Global Step:   8800, Training Batch Accuracy:  95.3%\n",
      "Global Step:   8900, Training Batch Accuracy:  98.4%\n",
      "Global Step:   9000, Training Batch Accuracy:  98.4%\n",
      "Global Step:   9100, Training Batch Accuracy:  98.4%\n",
      "Global Step:   9200, Training Batch Accuracy:  96.9%\n",
      "Global Step:   9300, Training Batch Accuracy: 100.0%\n",
      "Global Step:   9400, Training Batch Accuracy:  90.6%\n",
      "Global Step:   9500, Training Batch Accuracy:  92.2%\n",
      "Global Step:   9600, Training Batch Accuracy:  98.4%\n",
      "Global Step:   9700, Training Batch Accuracy:  96.9%\n",
      "Global Step:   9800, Training Batch Accuracy:  98.4%\n",
      "Global Step:   9900, Training Batch Accuracy:  98.4%\n",
      "Global Step:  10000, Training Batch Accuracy: 100.0%\n",
      "Time usage: 0:00:32\n"
     ]
    }
   ],
   "source": [
    "optimize(num_iterations=10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Accuracy on Test-Set: 90.7% (9069 / 10000)\n",
      "Example errors:\n"
     ]
    },
    {
     "data": {
      "image/png": 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hxNCKgRiZ+hGDMK3WuLbJWaZzuLIIGrJ70brruNltub26prUWNJGmiTgMBTyz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\nuGfVDa87AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fe0f9361400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix:\n",
      "[926   6  13   2   3   0   1   1  29  19] (0) airplane\n",
      "[  9 921   2   5   0   1   1   1   2  58] (1) automobile\n",
      "[ 18   1 883  31  32   4  22   5   1   3] (2) bird\n",
      "[  7   2  19 855  23  57  24   9   2   2] (3) cat\n",
      "[  5   0  21  25 896   4  24  22   2   1] (4) deer\n",
      "[  2   0  12  97  18 843  10  15   1   2] (5) dog\n",
      "[  2   1  16  17  17   4 940   1   2   0] (6) frog\n",
      "[  8   0  10  19  28  14   1 914   2   4] (7) horse\n",
      "[ 42   6   1   4   1   0   2   0 932  12] (8) ship\n",
      "[  6  19   2   2   1   0   1   1   9 959] (9) truck\n",
      " (0) (1) (2) (3) (4) (5) (6) (7) (8) (9)\n"
     ]
    }
   ],
   "source": [
    "print_test_accuracy(show_example_errors=True,\n",
    "                    show_confusion_matrix=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 关闭TensorFlow会话"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "现在我们已经用TensorFlow完成了任务，关闭session，释放资源。注意，我们需要关闭两个TensorFlow-session，每个模型对象各有一个。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# This has been commented out in case you want to modify and experiment\n",
    "# with the Notebook without having to restart it.\n",
    "# model.close()\n",
    "# session.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 总结\n",
    "\n",
    "之前的教程 #06 中，我们在一台笔记本电脑上花了15个小时来训练一个神经网络，用来对CIFAR-10数据集做分类，它在测试集上的准确率大约80%。\n",
    "\n",
    "在这篇教程中，我们使用教程 #07 中的Inception模型，来获取在CIFAR-10数据集上大概90%的分类准确率。我们将所有CIFAR-10数据集中的图像输入到Inception模型中，然后在最终分类层之前获取transfer-values。接着创建另外一个神经网络，它将transfer-values作为输入，生成一个CIFAR-10类别作为输出。\n",
    "\n",
    "CIFAR-10数据集包含60,000张图像。在一台没有GPU的电脑上，大约花了6个小时来计算Inception模型对这些图像的transfer-values。在这些transfer-values上训练一个新的分类器只需几分钟。两部分时间加起来，这种迁移学习比直接为CIFRA-10数据集训练一个神经网络要快一倍以上，并且它能得到更高的分类准确率。\n",
    "\n",
    "因此，用Inception模型做迁移学习，对于在自己的数据集上建立一个图像分类器是很有帮助的。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 练习\n",
    "\n",
    "下面使一些可能会让你提升TensorFlow技能的一些建议练习。为了学习如何更合适地使用TensorFlow，实践经验是很重要的。\n",
    "\n",
    "在你对这个Notebook进行修改之前，可能需要先备份一下。\n",
    "\n",
    "* 试着在PCA和t-SNE中使用整个训练集。会出现什么情况？\n",
    "\n",
    "* 试着为新的分类器改变神经网络。如果你删掉全连接层或添加更多的全连接层会发生什么？\n",
    "\n",
    "* 如果你执行更多或更少的迭代会出现什么情况？\n",
    "\n",
    "* 如果你改变优化器的`learning_rate`会发生什么？\n",
    "\n",
    "* 如果你像在教程#06中的那样，对CIFAR-10图像进行扭曲呢？你将不能使用缓存，因为每张图都不同。\n",
    "\n",
    "* 试着用MNIST数据集来代替CIFAR-10数据集。\n",
    "\n",
    "* 向朋友解释程序如何工作。\n"
   ]
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    "## License (MIT)\n",
    "\n",
    "Copyright (c) 2016 by [Magnus Erik Hvass Pedersen](http://www.hvass-labs.org/)\n",
    "\n",
    "Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n",
    "\n",
    "The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.\n",
    "\n",
    "THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE."
   ]
  }
 ],
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